Kurzgesagt – In a Nutshell
Sources - Why we hate each other on the internet
We thank the following experts:
Dr. Petter Törnberg
University of Amsterdam
Computational Social ScienceDr. Johanna Schindler
Ludwig-Maximilians-Universität München
Institut für Kommunikationswissenschaft und Medienforschung
Prof. Mario Haim
Ludwig-Maximilians-Universität München
Institut für Kommunikationswissenschaft und Medienforschung
Prof. Barbara F. Walter
School Of Global Policy And Strategy, UC San Diego
This script was inspired by the following publication
#Petter Törnberg. How digital media drive affective polarization through partisan sorting. 2022.
https://www.pnas.org/doi/epdf/10.1073/pnas.2207159119
– In 2022 nearly half of Americans expected a civil war in the next few years, one in five now believes political violence is justified.
These percentages are based on a recent survey done with more than 8600 adults in the US. The findings are then extrapolated to the entire population through statistical methods.
#Wintemute et al., Views of American Democracy and Society and Support for Political Violence: First Report from a Nationwide Population-Representative Survey. 2022.
https://www.medrxiv.org/content/10.1101/2022.07.15.22277693v1.full.pdf
Quote: “Results The analytic sample included 8,620 respondents; 50.6% (95% Confidence Interval (CI) 49.4%, 51.7%) were female; mean (SD) age was 48.4 (18.0) years. Two-thirds of respondents (67.2%, 95% CI 66.1%, 68.4%) perceived “a serious threat to our democracy,” but more than 40% agreed that “having a strong leader for America is more important than having a democracy” and that “in America, native-born white people are being replaced by immigrants.” Half (50.1%) agreed that “in the next few years, there will be civil war in the United States.”
[...].
One in 5 respondents (20.5%) believed that “in general,” political violence was at least sometimes justified; 3.0% considered it usually or always justified (Table 5, Figure 1).”
The tables which represent the relevant survey results to the script are as follows:
https://www.medrxiv.org/content/10.1101/2022.07.15.22277693v1.full.pdf
NOTE: In the making of this video, the preprint paper above was published in a peer review journal where the text is partly modified. The data is the same in the preprint and peer-reviewed versions. We stick to the text and the interpretation in the preprint – which includes “Somewhat agree” in the total percentage, whereas the peer-reviewed version does not do so. (Relevant sentences to this script which were modified are underlined in the following quote from the peer-reviewed version):
https://pubmed.ncbi.nlm.nih.gov/37770994/
Quote: “Results: The analytic sample included 8620 respondents; 50.5% (95% confidence interval (CI) 49.3%, 51.7%) were female; and weighted mean (± standard deviation) age was 48.4 (± 18.0) years. Nearly 1 in 5 (18.9%, 95% CI 18.0%, 19.9%) agreed strongly or very strongly that "having a strong leader for America is more important than having a democracy"; 16.2% (95% CI 15.3%, 17.1%) agreed strongly or very strongly that "in America, native-born white people are being replaced by immigrants," and 13.7% (95% CI 12.9%, 14.6%) agreed strongly or very strongly that "in the next few years, there will be civil war in the United States." One-third of respondents (32.8%, 95% CI 31.7%, 33.9%) considered violence to be usually or always justified to advance at least 1 of 17 specific political objectives.
Only 3.0% (95% CI 2.6%, 3.6%) considered political violence to be usually or always justified “in general” (Table 6, Fig. 1). In most cases, slightly larger proportions of respondents considered violence to be usually or always justified to advance each of 17 specific political objectives considered individually (Tables 6, 7). Among those 17 objectives, support was most common for violence “to preserve an American way of life I believe in” (12.1%; 95% CI, 11.3%, 12.9%).”
Corresponding data tables from the peer-reviewed publication for comparison:
#Table 3 Beliefs concerning the potential need for violence in the USA
https://link.springer.com/article/10.1186/s40621-023-00456-3/tables/3
#Table 6 Justification for political violence, in general and for 9 specific objectives
https://link.springer.com/article/10.1186/s40621-023-00456-3/tables/6
It is important to note that these numbers may not necessarily represent the entire population accurately.
#Rodrigo Pérez Ortega. Half of Americans anticipate a U.S. civil war soon, survey finds. 2022
Quote: “Barbara Walter, a political scientist at the University of California, San Diego, who was also not involved in the study, agrees. But she suspects the survey responses overrepresent the number of Americans who would be willing to turn to violence because, she says, surveys tend to overstate what people actually think. “The numbers always tend to be shocking, but in essence, are probably not true.”
– And it is not just the US but around the world. People increasingly see themselves as part of opposing teams.
Unfortunately, this has been observed in other countries. There is already a good amount of literature studying the dynamics in different countries.
#Thomas Carothers, Andrew O’donohue. How to Understand the Global Spread of Political Polarization. 2019.
Quote: “A lot of research shows how populist and illiberal leaders are putting democracy in danger. But it rarely addresses what we feel is a more fundamental, underlying problem: severe political polarization.
Polarization is tearing at the seams of democracies around the world, from Brazil and India to Poland and Turkey. It isn’t just an American illness; it’s a global one.
We wanted to know: Why has polarization come to a boil in so many places in recent years? Are there any telling similarities in the patterns of polarization across different countries? And perhaps most importantly, once societies have become deeply polarized, what can they do to start healing their divisions?”
#McCoy, J., Rahman, T., & Somer, M.Polarization and the Global Crisis of Democracy: Common Patterns, Dynamics, and Pernicious Consequences for Democratic Polities. 2018.
https://journals.sagepub.com/doi/10.1177/0002764218759576
Quote: “This article argues that a common pattern and set of dynamics characterizes severe political and societal polarization in different contexts around the world, with pernicious consequences for democracy. Moving beyond the conventional conceptualization of polarization as ideological distance between political parties and candidates, we offer a conceptualization of polarization highlighting its inherently relational nature and its instrumental political use. Polarization is a process whereby the normal multiplicity of differences in a society increasingly align along a single dimension and people increasingly perceive and describe politics and society in terms of “Us” versus “Them.””
#Gidron, N., Adams, J., & Horne, W. Toward a comparative research agenda on affective polarization in mass publics. 2019.
Quote: “We address two issues. First, we report descriptive statistics based on analyses of survey data from twenty western democracies, which suggest that affective polarization in the United States is not especially intense compared to other Western polities. This finding may be welcomed by Americans (who may be glad that they are not extremely affectively polarized in comparative perspective), while it may dismay citizens of many other western democracies (who may be disappointed that they are as intensely polarized as the US). In either case we find this comparison instructive. Second, and related, we argue for the advantages of analyzing American affective polarization within a comparative context.”
#Laura Silver. Pew Research Center. Most across 19 countries see strong partisan conflicts in their society, especially in South Korea and the U.S. 2022.
Quote: “In other nations, perceived political divisions are increasing. Since 2021, there have been substantial increases in the share of adults who see strong political divisions in the Netherlands, Canada, the United Kingdom, Germany, Singapore, Spain, France, Sweden and Belgium.”
– Social media divides us, makes us more extreme and less empathetic, it riles us up or sucks us into doom scrolling, making us stressed and depressed. It feels like we need to touch grass and escape to the real world.
Social media use can affect mental health through a variety of mechanisms. Envy is one that can have negative implications for users. A broad set of studies found that social media is at least partly involved in developing anxiety and depression.
#Karim, Fazida, et al. Social media use and its connection to mental health: a systematic review. 2020.
Quote: “This systematic review has found that social media envy can affect the level of anxiety and depression in individuals. In addition, other potential causes of anxiety and depression have been identified, which require further exploration.”
#Jonathan Haidt. More Social Media Regulation. 2019.
https://www.stern.nyu.edu/experience-stern/faculty-research/more-social-media-regulation
Quote: “But there’s another route by which social media may soon begin imposing a heavy new cost on American democracy: It appears to have contributed to the rapid rise in depression and anxiety among Gen Z (born in 1996 and later). The rise began around 2012, not just in the United States but also in the UK and Canada. With Jean Twenge, the author of iGen, I have been collecting and categorizing the available evidence on this question, and a clear pattern has emerged: Heavy use (but not light to moderate use) of social media (as opposed to “screen time” more generally) is consistently associated with depression, anxiety and self-harm, particularly for girls. The evidence is not just correlational; five experiments have randomly assigned people to cut back on social media use; all found at least some beneficial outcomes.”
Doom-scrolling is a term that’s being used to describe a deliberate extended exposure to negative news. It is linked to negative effects on mental health. But even shorter exposure to negative news can have emotional consequences:
# Buchanan, Kathryn, et al. "Brief exposure to social media during the COVID-19 pandemic: Doom-scrolling has negative emotional consequences, but kindness-scrolling does not." 2021.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257728
Quote: “[...] the current research demonstrates that as little as two minutes of exposure to negative news about COVID-19 can have negative consequences. [...] we show that it is not simply that time spent on social media is problematic, but rather that consumption of negative news is the source of concern.”
– New research shows that we might have largely misinterpreted why this is the case.
It turns out that the social media internet may uniquely undermine the way our brains work but not in the way you think.
We were inspired largely by the following paper and it also summarizes the new research that encapsulates the main idea in this script. We provide more research and supporting ideas further below for the other parts of the script, but the following section from the paper is a good opening summary for the rest of the script. Basically, contrary to the common belief that it isolates us into echo-chambers, digital media actually has increased the amount of opposing views we are exposed to, and the levels of conflicts too overwhelming to deal with. This has not necessarily made us more moderate or see things in a different perspective. Rather, it leads to the alignment of the various conflicts along a single division, like partisan identity, making the perceived differences larger than they actually are and feeds in the polarization.
#Petter Törnberg. How digital media drive affective polarization through partisan sorting. 2022.
https://www.pnas.org/doi/epdf/10.1073/pnas.2207159119
Quote: “In the media literature, the fundamental mechanism for explaining the impact of new media technology on politics has been selective exposure, captured in notions such as echo chambers or filter bubbles: media technologies are said to polarize by allowing us to isolate ourselves with like minded others, thus avoiding the discomfort of being exposed to views and ideas from other groups. Since interacting with opposing viewpoints is thought to be central to moderating opinions, the result is said to be more extreme issue positions (13).”
However, this hypothesis has become increasingly questioned as two empirical findings question the two fundamental assumptions of this mechanism: first, results show that digital media is in fact characterized by substantial interaction across partisan lines (26); second, such interaction with opposing views has been shown to not necessarily reduce polarization, as psychological mechanisms allow individuals to disregard messages from individuals whom they deem different (75). These findings capture the intuitive observation that while digital media are rife with contentious debate, these rarely lead to individuals moderating their positions, let alone being convinced by opposing arguments. While we may interact and consume information from across the ideological divide, such bipartisan exchange is not necessarily an expression of good faith attempts at seeing things through another perspective. The suggestion of this paper has been that these two points of empirical evidence may not only be reason to reject the echo chamber hypothesis (26), but that they also provide the foundation for an alternative emergent causal mechanism underlying the polarizing effects of digital media.”
The Myth of the Filter Bubble
–You probably heard about online filter bubbles: Algorithms give you exactly what you want, or what they think you want. You only see information that shows you opinions that agree with yours, while dissenting opinions or information are filtered out.
The definition of the term ‘filter bubble’ goes back to 2011 when popularized through the book The Filter Bubble: What the Internet Is Hiding from You by Eli Pariser. Initially, the term was covering the algorithmic personalization of various search results, not necessarily social media content.
# Eli Pariser. Author Q&A with Eli Pariser.
Quote: “Your filter bubble is this unique, personal universe of information created just for you by this array of personalizing filters. ”
Even though the term has been used widely since then, it has not been clearly defined across contexts. Moreover it has been used interchangeably with other terms like ‘echo chambers’ as social media platforms joined the internet diets of people across the globe. The lack of a commonly accepted definition hindered and blurred the debate and the research around the existence of filter bubbles and echo chambers.
In their glossary, European Center for Populism Studies defines these terms as follows:
#The European Center for Populism Studies. Dictionary Of Populism. Retrieved October, 2023.
https://www.populismstudies.org/Vocabulary/echo-chamber/
Quote: “Echo chamber is a metaphorical description of a situation in which beliefs are amplified or reinforced by communication and repetition inside a closed system. By visiting an ‘echo chamber’, people are able to seek out information that reinforces their existing views, potentially as an unconscious exercise of confirmation bias. This may increase social and political polarization and extremism.”
Quote: “It is important to distinguish the difference between echo chambers and filter bubbles. Both concepts relate to the ways individuals are exposed to content devoid of clashing opinions, and colloquially might be used interchangeably. However, echo chamber refers to the overall phenomenon by which individuals are exposed only to information from like-minded individuals, while filter bubbles are a result of algorithms that choose content based on previous online behavior, as with search histories or online shopping activity.”
Another set of definitions of these terms, exclusively in the context of social media, came from Axel Brun who also pointed out that the lack of concrete definitions has debilitated scientific research on these terms and rejected the existence of filter bubbles and echo chambers.
#Axel Bruns. Filter Bubble. 2019.
https://policyreview.info/concepts/filter-bubble
Quote: “While further research should confirm these results for a greater number of national contexts and a broader range of search engines and news portals, at least for search, it seems that the filter bubble idea has deflated: far from the vision (or threat) of an individually unique Daily Me, personalisation in general and news specific search results still appears to be exceptionally limited. For social media, on the other hand, the debate about filter bubbles and echo chambers continues, with various studies both supporting and denying their existence. Here, the definitional confusion is most acutely felt, and also manifests very differently across the different disciplines that are involved in testing these concepts.
For the purpose of the following discussion, and in order to introduce a meaningful distinction between the ‘echo chamber’ and ‘filter bubble’ concepts, we might employ the following minimal definitions (cf. Bruns, 2019, p.29):
echo chamber: emerges when a group of participants choose to preferentially connect with each other, to the exclusion of outsiders (e.g., by friending on Facebook, following on Twitter, etc.)
filter bubble: emerges when a group of participants choose to preferentially communicate with each other, to the exclusion of outsiders (e.g., by comments on Facebook, @mentions on Twitter, etc.)”
#Richard Fletcher. The truth behind filter bubbles: Bursting some myths. 2020
https://reutersinstitute.politics.ox.ac.uk/news/truth-behind-filter-bubbles-bursting-some-myths
Quote: “I personally think that echo chambers and filter bubbles are slightly different. An echo chamber is what might happen when we are overexposed to news that we like or agree with, potentially distorting our perception of reality because we see too much of one side, not enough of the other, and we start to think perhaps that reality is like this.
Filter bubbles describe a situation where news that we dislike or disagree with is automatically filtered out and this might have the effect of narrowing what we know. This distinction is important because echo chambers could be a result of filtering or they could be the result of other processes, but filter bubbles have to be the result of algorithmic filtering.”
It is then important to check in which meaning these terms are used in publications before interpreting the results as to whether filter bubbles and echo chambers exist.
#Sebastian Randerath. Myth #22: We all live in filter bubbles. 2019.
https://www.internetmythen.de/en/index39c5.html?mythen=myth-22-we-all-live-in-filter-bubbles
Quote: “Today, Pariser’s filter bubble is used to explain different social, economic and digital phenomena like the growth of populism, hate speech, fake news, growing capitalism and even depression. Often the concept of the echo chamber that existed long before the filter bubble and had been already employed by Marshall McLuhan to describe the resonating world of tribal cultures (McLuhan/Norden 1969: 72) is misused to extend the concept of being (consciously or automatically) separated from dissenting world views on social media platforms. Filter bubbles and echo chambers have become blurry concepts to simplify different and complex phenomena of decision-making and formation of public opinion.”
– Since you only see content close to your world view, more extreme and toxic opinions suddenly seem less extreme. You are trapped in a radicalising filter bubble and your view of the world becomes more narrow and extreme.
When you see only or dominantly more content that is close to your world view, you miss out on the whole spectrum of opinions, which is balanced between similar and opposing ideas to yours. But when the opposing side is not visible, you might find the more extreme or even toxic opinions on your side less extreme and disturbing than they are.
There are various mechanisms underlying how filter bubbles drive polarization and there has been accumulating literature of the underlying mechanisms but there have been two basic underlying assumptions (which are challenged with the new research mentioned above previously):
1- digital media lock people into isolated echo chambers
2- homogeneous groups lead to extreme opinions, while interaction with opposing ideas or individuals leads to political moderation.
In the following paper, the author explains how the echo chambers lead to polarization.
#Cass R. Sunstein. The Law of Group Polarization. 1999
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=199668
Quote: “In a striking empirical regularity, deliberation tends to move groups, and the individuals who compose them, toward a more extreme point in the direction indicated by their own predeliberation judgments. For example, people who are opposed to the minimum wage are likely, after talking to each other, to be still more opposed; people who tend to support gun control are likely, after discussion, to support gun control with considerable enthusiasm; people who believe that global warming is a serious problem are likely, after discussion, to insist on severe measures to prevent global warming. This general phenomenon -- group polarization -- has many implications for economic, political, and legal institutions. It helps to explain extremism, "radicalization," cultural shifts, and the behavior of political parties and religious organizations; it is closely connected to current concerns about the consequences of the Internet; it also helps account for feuds, ethnic antagonism, and tribalism.”
– Extreme filter bubbles seem to be exceedingly rare.
Studies looking into the effect of filter bubbles have found various degrees of filter bubbles depending on the platform or the medium people get their news from. But it has not been found to affect the majority of the users rather a smaller percentage varying across platforms. A number of studies that checked the news aggregation websites and browser traffic of people did not confirm the idea that the majority of users are exposed to congenial content and not hearing other voices.
There are several important points to keep in mind regarding the research. First, one needs to consider that almost all studies are using data samples from the US. So we work with the assumption that we can generalize based on the findings in the US. Second, there is no consensus in the field regarding the degree of echo chambers and it is still highly debated. This is partly due to the different datasets collected from different platforms, time-frame of data collection, lack of a common definition of “filter bubble” or "echo chamber”, different methods used (such as surveys, modeling, real user activity vs. accounts created by researchers). Also, not the same type of data is readily available across platforms, the type of data available from Twitter may not be available from Facebook. Also, the use of platforms and activity patterns change quite fast in digital media, especially in the last decade, which creates a lag between the research findings and the current state of digital media consumption. Therefore, even though there is no unequivocal acceptance, the emerging research suggests that filter bubbles are not dictating the levels of polarization that we observe today and are not encapsulating the larger population. They seem to influence a smaller and more politically active group of users, which tend to be in the extremes of the spectrum. But it also does mean that this is letting the social media off the hook in its role in polarization, it is just that the underlying mechanism does not appear to be the filter bubble.
# Sebastian Randerath. Myth #22: We all live in filter bubbles.
https://www.internetmythen.de/en/index39c5.html?mythen=myth-22-we-all-live-in-filter-bubbles
Quote: “Filter bubbles do not run our lives. Personalized filtering by algorithms is not the cause for public opinion formation and has merely trivial effects on search results with major search engines. The concept is mainly used as a metaphor to reduce the complexity of social, economic and technological dynamics on platforms and public debates, but is of little value beyond that.”
#Markus Prior. Media and Political Polarization. 2013.
https://www.annualreviews.org/doi/abs/10.1146/annurev-polisci-100711-135242
Quote: “This article examines if the emergence of more partisan media has contributed to political polarization and led Americans to support more partisan policies and candidates. Congress and some newer media outlets have added more partisan messages to a continuing supply of mostly centrist news. Although political attitudes of most Americans have remained fairly moderate, evidence points to some polarization among the politically involved. Proliferation of media choices lowered the share of less interested, less partisan voters and thereby made elections more partisan. But evidence for a causal link between more partisan messages and changing attitudes or behaviors is mixed at best. Measurement problems hold back research on partisan selective exposure and its consequences. Ideologically one-sided news exposure may be largely confined to a small, but highly involved and influential, segment of the population. There is no firm evidence that partisan media are making ordinary Americans more partisan.”
In the following study, authors looked into the ideological exposure through observing the accounts followed by a representative sample of 1500 Twitter users during 2016 elections in the US. They also found out that the people on ideological extremes are more politically engaged in their following behavior on Twitter.
#Eady, G., Nagler, J., Guess, A., Zilinsky, J., & Tucker, J. A. (2019). How Many People Live in Political Bubbles on Social Media? Evidence From Linked Survey and Twitter Data.
https://journals.sagepub.com/doi/10.1177/2158244019832705
Quote: “In this article, we measure the ideological distribution of both Twitter accounts followed and tweets potentially seen at the individual level. We analyze data from a nationally representative survey of Americans with linked data on respondents’ Twitter IDs, which allows us to collect the set of accounts that they followed and all tweets posted by those accounts. We quantify how many respondents live in online ideological “bubbles” based on their own self-reported ideology. We find a substantial amount of overlap in the ideological distributions of accounts followed by users on opposite ends of the political spectrum. In addition to this relative similarity in overall following patterns, however, many individuals’ willingness to purposefully venture into challenging spaces is limited, although an analysis encompassing all potentially seen tweets shows approximately twice as much cross-cutting exposure—an effect that is somewhat larger when focusing on retweets from other accounts.”
In the following study, the authors looked into the web-browsing patterns of 50,000 regular online-news readers in the US in 2013. Their findings suggest that the social networks and search engines increase the mean ideological distance between individuals, but they also increase the exposure to news from the opposite side of the spectrum. Therefore the authors found both supporting and clashing evidence, with modest magnitudes of the effects in both cases.
#Seth Flaxman, Sharad Goel, Justin M. Rao. Filter Bubbles, Echo Chambers, And Online News Consumption. 2016
https://academic.oup.com/poq/article/80/S1/298/2223402
Quote: “Summarizing our results on ideological isolation, we find that individuals generally read publications that are ideologically quite similar, and moreover, users that regularly read partisan articles are almost exclusively exposed to only one side of the political spectrum. In this sense, many— indeed nearly all—users exist in so-called echo chambers. We note, however, two key differences between our findings and some previous discussions of this topic (Pariser 2011; Sunstein 2009). First, we show that while social media and search do appear to contribute to segregation, the lack of withinuser variation seems to be driven primarily by direct browsing. Second, consistent with Gentzkow and Shapiro (2011), the outlets that dominate partisan news coverage are still relatively mainstream, ranging from the New York Times on the left to Fox News on the right; the more extreme ideological sites (e.g., Breitbart), which presumably benefited from the rise of online publishing, do not appear to qualitatively impact the dynamics of news consumption.”
Quote: “To help explain these results, we note that while sharing information is popular on social media, the dissemination of news is not its primary function. In fact, we find that only 1 in 300 clicks of links posted on Facebook lead to substantive news articles; rather, the vast majority of these clicks go to video- and photo-sharing sites. Moreover, we observe that even the most extreme segregation that we see (0.20 for opinion articles returned by search engines) is not, in our view, astronomically high. In particular, that level of segregation corresponds to the ideological distance between Fox News and Daily Kos, which represents meaningful differences in coverage (Baum and Groeling 2008) but is within the mainstream political spectrum. Consequently, though the predicted filter bubble and echo chamber mechanisms do appear to increase online segregation, their overall effects at this time are somewhat limited.”
#De Francisci Morales, G., Monti, C. & Starnini, M. No echo in the chambers of political interactions on Reddit. 2021.
https://www.nature.com/articles/s41598-021-81531-x
Quote: “Overall, our findings show that Reddit has been a tool for political discussion between opposing points of view during the 2016 elections. This behavior is in stark contrast with the echo chambers observed in other polarized debates regarding different topics, on several social media platforms. While it has been argued that polarization on social media can result in the presence of echo chambers, in which users do not hear opposing views, here we observe the reversed phenomenon: polarization is associated to increased interactions between groups holding opposite opinions. However, this relation between polarization and heterophily might not go beyond the digital realm. Reportedly, people perceive to encounter more disagreement in online than in offline interactions42. Further research should be dedicated to understanding whether the heterophily found in this social network is specific about the 2016 presidential elections, or it applies to politics in general, and thus it might be a general feature of the Reddit platform14.”
In 2015, Facebook data science team published a study one of the main findings of which was that the individual choices play a more significant role than the algorithmic ranking in limiting the amount of cross-cutting content.
#Bakshy, Messing and Adamic. Exposure to ideologically diverse news and opinion on Facebook. 2015.
Quote: “The order in which users see stories in the News Feed depends on many factors, including how often the viewer visits Facebook, how much they interact with certain friends, and how often users have clicked on links to certain websites in the News Feed in the past. We found that after ranking, there is on average slightly less cross cutting content: The risk ratio comparing the probability of seeing cross-cutting content relative to ideologically consistent content is 5% for conservatives and 8% for liberals (supplementary materials, section S1.7). Individual choice further limits exposure to ideologically cross-cutting content. After adjusting for the effect of position [the click rate on a link is negatively correlated with its position in the News Feed (fig. S5)], we estimated the risk ratio comparing the likelihood that an individual clicks on a cross-cutting content relative to a consistent content to be 17% for conservatives and 6% for liberals, a pattern that is consistent with prior research (4, 17). Despite these tendencies, there is substantial room for individuals to consume more media from the other side; on average, viewers clicked on 7% of hard content available in their feeds.”
Quote: “Within the population under study here, individual choices (2, 13, 15, 17) more than algorithms (3, 9) limit exposure to attitude-challenging content in the context of Facebook. Despite the differences in what individuals consume across ideological lines, our work suggests that individuals are exposed to more cross-cutting discourse in social media than they would be under the digital reality envisioned by some (2, 6). Rather than people browsing only ideologically aligned news sources or opting out of hard news altogether, our work shows that social media expose individuals to at least some ideologically crosscutting viewpoints (4).”
Eli Pariser, who had written about the filter bubble extensively, gave his take on the 2015 Science study above, mentioning that even though the study found that filter bubbles exist, they were smaller than he had initially guessed.
#Eli Pariser. Did Facebook’s Big New Study Kill My Filter Bubble Thesis? 2015.
Quote: ”Here’s the upshot: Yes, using Facebook means you’ll tend to see significantly more news that’s popular among people who share your political beliefs. And there is a real and scientifically significant “filter bubble effect” — the Facebook news feed algorithm in particular will tend to amplify news that your political compadres favor.
This effect is smaller than you might think (and smaller than I’d have guessed.) On average, you’re about 6% less likely to see content that the other political side favors. Who you’re friends with matters a good deal more than the algorithm.”
Another important thing to note is that the filter bubble literature generally capitalizes on online news and more research is needed to rule out the effect of filter bubbles in social media.
#Ro’ee Levy. Social Media, News Consumption, and Polarization: Evidence from a Field Experiment. 2021
https://pubs.aeaweb.org/doi/pdfplus/10.1257/aer.20191777
Quote: “This paper contributes to the literature on social media and news consumption. In his seminal book The Filter Bubble, Eli Pariser warned that the “era of personalization is here” (Pariser 2011, p. 19). However, recent reviews concluded that “we lack convincing evidence of algorithmic filter bubbles in politics” (Guess et al. 2018, p. 12). Papers in this literature typically estimate segregation in online news based on cross-sectional analysis of browsing behavior (Gentzkow and Shapiro 2011; Flaxman, Goel, and Rao 2016; Peterson, Sharad, and Iyengar 2019; Guess forthcoming). Since they lack social media data, these papers cannot measure segregation within one’s social media feed. One exception is a paper analyzing Facebook data, arguing that exposure to counter-attitudinal news shared by friends is mostly limited by individual choices and not by algorithmic ranking (Bakshy, Messing, and Adamic 2015). The paper analyzes large data but does not exploit exogenous
variation. I advance the literature by generating experimental variation in subscriptions to outlets and collecting data on exposure to posts from those outlets. This allows me to decompose the mechanisms limiting exposure to counter-attitudinal news and demonstrate the existence of a filter bubble, i.e., that Facebook’s algorithm is more likely to expose individuals to news matching their ideology, conditional on subscription.”
#Guess, Nyhan, Lyons, Reifler. Avoiding The Echo Chamber About Echo Chambers.
Quote: “Technology can in some cases facilitate or worsen echo chambers, but the findings are more subtle than many popular accounts imply. One frequently cited culprit is Twitter, which is often used as a proxy for social media due to the ease of studying it compared to Facebook (where posts are largely private). For instance, an analysis of the Twitter conversation about the 2010 U.S. congressional midterm elections found that retweet networks were highly segregated by ideology (Conover et al. 2011). In general, Americans with extreme views are more likely to be embedded in homogeneous Twitter networks (Boutyline and Willer 2017) and may tend to dominate online conversations (Barberá and Rivero 2014). However, only a small fraction of the population is on Twitter, as noted above, and Twitter users are exposed to cross-cutting content that they are unlikely to re-broadcast, but to which they may respond (Conover et al. 2011; see also Karlsen et al. 2017). This
exposure to cross-cutting content often occurs via “weak ties” revealed by social media (Granovetter 1973). In this way, Twitter and other social media platforms embed most users in ideologically diverse networks which could even reduce mass polarization over time (Barberá N.d.). In addition, other work shows that public conversations on Twitter about political events, such as elections, are likely to resemble echo chambers among ideologically similar users, but those concerning other current events are more inclusive (Barberá et al. 2015). ”
NOTE: In the following study which was conducted in collaboration with Facebook (data provided by Meta), authors looked into Facebook traffic of the entire population of active users of the platform in the USA in 2020. They found out that even though the content from politically like-minded sources (sources being friends, Pages, and groups) constitutes a big chunk of what people see on the platform, there is only a small group of users who are exclusively exposed to content from like-minded sources: 1 in 5 users get more than three fourths of their exposures from like-minded sources. (The classification algorithm used to determine the like-mindedness is trained to predict the self-reported ideology users based on their demographics, preferred language, location, and engagement with content, Pages, and groups. But the classifier itself was not disclosed in the paper) Because of this we have not included this study in our script.
#Nyhan, B., Settle, J., Thorson, E. et al. Like-minded sources on Facebook are prevalent but not polarizing. 2023.
https://www.nature.com/articles/s41586-023-06297-w
Quote: “We find that the median Facebook user received a majority of their content from like-minded sources—50.4% versus 14.7% from cross-cutting sources (the remainder are from friends, Pages and groups that we classify as neither like-minded nor cross-cutting). Like-minded exposure was similar for content classified as ‘civic’ (that is, political) or news (see Supplementary Information, section 4.3 for details on the classifiers used in this study). The median user received 55% of their exposures to civic content and 47% of their exposures to news content from like-minded sources (see Extended Data Table 1 for exact numbers and Supplementary Fig. 3 for a comparison with our experimental participants). Civic and news content make up a relatively small share of what people see on Facebook, however (medians of 6.9% and 6.7%, respectively; Supplementary Table 11).”
Despite the prevalence of like-minded sources in what people see on Facebook, extreme echo chamber patterns of exposure are infrequent. Just 20.6% of Facebook users get over 75% of their exposures from like-minded sources. Another 30.6% get 50–75% of their exposures on Facebook from like-minded sources. Finally, 25.6% get 25–50% of their exposures from like-minded sources and 23.1% get 0–25% of their exposures from like-minded sources. These proportions are similar for the subsets of civic and news content (Extended Data Table 1). For instance, like-minded sources are responsible for more than 75% of exposures to these types of content for 29% and 20.6% of users, respectively. However, exposure to content from cross-cutting sources is also relatively rare among Facebook users. Only 32.2% have a quarter or more of their Facebook Feed exposures coming from cross-cutting sources (31.7% and 26.9%, respectively, for civic and news content).”
To check the effects of like-minded content on the political attitude of the users, authors designed an intervention on 23,377 users on the platform prior to 2016 US elections, whereby they decreased the exposure to like-minded content by a third. They found that the intervention increased the exposure from cross-cutting sources and decreased uncivil language, but had no measurable effects such as affective polarization, ideological extremity, candidate evaluations and belief in false claims.
Quote: “Finally, we found that reducing exposure to content from like-minded sources on Facebook had no measurable effect on a range of political attitudes, including affective polarization, ideological extremity and opinions on issues; our exploratory equivalence bounds analyses allow us to confidently rule out effects of ±0.12 s.d. We were also unable to reject the null hypothesis in any of our tests for heterogeneous treatment effects across many distinct subgroups of participants.”
Some researchers however pointed out to the potential lack of data transparency due to the collaboration with Meta.
#Nix, Johnson and Zakrzewski. Changing Facebook’s algorithm won’t fix polarization, new study finds. 2023.
https://www.washingtonpost.com/technology/2023/07/27/social-media-research-meta-political-views/
Quote: “Tucker, of New York University, cautioned against reading too much into the research. “It’s possible that if we did a similar study at another period of time or in another country where people were not paying as much attention to politics or not being as inundated with other information from other sources about politics, we would have found a different result,” he said.
The study also was conducted in a world in which, in many ways, the cat was already out of the bag. A three-month switch in how information is served on a social network occurred in the context of a long-standing change in how people share and find information.
“This finding cannot tell us what the world would have been like if we hadn’t had social media around for the last 10 to 15 years,” Tucker said.”
The following commentary on the study above as well as the other three studies which were published in collaboration with Meta recently, summarizes findings and the potential caveats.
#Jeff Tollefson. Tweaking Facebook feeds is no easy fix for polarization, studies find. 2023.
https://www.nature.com/articles/d41586-023-02420-z
Quote: “The authors say that all of the data that were collected will be available for researchers. Nonetheless, some academics question the model, in part because it depends entirely on the willingness of Meta to participate.
The research represents an important leap forward, but scientists still had only a partial view into the Meta universe, says Michael Wagner, a political scientist at the University of Wisconsin–Madison who served as an independent rapporteur for the project. Wagner notes that many of the individual data were off-limits, and even the data that the scientists were able to access came pre-packaged by Meta. What is needed, he says, is a system that allows access to the raw data and offers incentives to researchers at Meta to collaborate.”
– Other studies that checked at what people actually look at online or are shown by search engines, found little evidence that you are ideologically isolated.
Following study checked the effect of personalization on the diversity of articles on the news aggregator GoogleNews and did not find substantial support for the existence of a filter bubble.
#Mario Haim, Andreas Graefe, Hans-Bernd-Brosius. Burst of the Filter Bubble?: Effects of personalization on the diversity of Google News. 2018.
Quote: “In offering personalized content geared towards users’ individual interests, recommender systems are assumed to reduce news diversity and thus lead to partial information blindness (i.e., filter bubbles). We conducted two exploratory studies to test the effect of both implicit and explicit personalization on the content and source diversity of Google News. Except for small effects of implicit personalization on content diversity, we found no support for the filter-bubble hypothesis. We did, however, find a general bias in that Google News over-represents certain news outlets and under-represents other, highly frequented, news outlets. The results add to a growing body of evidence, which suggests that concerns about algorithmic filter bubbles in the context of online news might be exaggerated.”
In the following study, the author looked into the internet browsing histories of 1392 and 654 people during early 2015 and from October 2016 -shortly before the U.S. presidential election- respectively, and found that the news diets of democrats and republicans were largely overlapping.
# Andrew M. Guess. (Almost) Everything in Moderation: New Evidence on Americans' Online Media Diets. 2021.
https://onlinelibrary.wiley.com/doi/epdf/10.1111/ajps.12589
Quote: “Does the internet facilitate selective exposure to politically congenial content? To answer this question, I introduce and validate large-N behavioral data on Americans’ online media consumption in both 2015 and 2016. I then construct a simple measure of media diet slant and use machine classification to identify individual articles related to news about politics. I find that most people across the political spectrum have relatively moderate media diets, about a quarter of which consist of mainstream news websites and portals. Quantifying the similarity of Democrats’ and Republicans’ media diets, I find nearly 65% overlap in the two groups’ distributions in 2015 and roughly 50% in 2016. An exception to this picture is a small group of partisans who drive a disproportionate amount of traffic to ideologically slanted websites. If online “echo chambers” exist, they are a reality for relatively few people who may nonetheless exert disproportionate influence and visibility.”
#Duggan and Smith. Political content on social media. 2016
https://www.pewresearch.org/internet/2016/10/25/political-content-on-social-media/
Quote: “But for many users, friend networks that encompass a range of political beliefs are the norm. Roughly half of Facebook users (53%) and more than one-third of Twitter users (39%) say that there is a mix of political views among the people in their networks. And an additional 5% of Facebook users and 6% of Twitter users indicate that most of the people they associate with in these spaces hold different political beliefs from their own (Note: a Pew Research Center survey of news consumption habits conducted in 2014 similarly found that Facebook users are exposed to a relatively broad range of posts that they agree and disagree with).”
– It is the exact opposite: Online you are constantly confronted with opinions and world views that are not your own.
Besides seeing what you like, you are constantly exposed to views different than yours. While that technically sounds not necessarily bad, it might be part of the reason underlying polarization.
Bail et al. Exposure to opposing views on social media can increase political polarization. 2018
https://www.pnas.org/doi/10.1073/pnas.1804840115
Quote: “There is mounting concern that social media sites contribute to political polarization by creating “echo chambers” that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in which they were offered financial incentives to follow a Twitter bot for 1 month that exposed them to messages from those with opposing political ideologies (e.g., elected officials, opinion leaders, media organizations, and nonprofit groups). Respondents were resurveyed at the end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative posttreatment. Democrats exhibited slight increases in liberal attitudes after following a conservative Twitter bot, although these effects are not statistically significant. Notwithstanding important limitations of our study, these findings have significant implications for the interdisciplinary literature on political polarization and the emerging field of computational social science.”
– It turns out the place where you are the most ideologically isolated is your real life, in the real world, with real people. Your online bubble is much more diverse than your real world interactions with your friends, families, colleagues and neighbours. The filter bubble exists in your real life, not online.
In the following study, authors calculated the isolation index, which is the difference between the average conservative exposure of conservatives and the average conservative exposure of liberals. To compare isolation indices across different social contexts media outlets. They combined social survey data with online and offline news consumption activity of thousands of US internet users during 2009. They found that even though the internet new consumption has a higher isolation index than the offline news outlets (tv, magazines, local newspapers), it is lower than that of the “real life” networks.
#Gentzkow And Shapiro. Ideological Segregation Online And Offline. 2011
https://web.stanford.edu/~gentzkow/research/echo_chambers.pdf
Quote: “The isolation index we estimate for the Internet is higher than that of broadcast television news (1.8), cable television news (3.3), magazines (4.7), and local newspapers (4.8) and lower than that of national newspapers (10.4). We estimate that eliminating the Internet would reduce the ideological segregation of news and opinion consumption across all media from 5.1 to 4.1. Online segregation is somewhat higher than that of a social network where individuals matched randomly within counties (5.9) and lower than that of a network where individuals matched randomly within ZIP codes (9.4). It is significantly lower than the segregation of actual networks formed through voluntary associations (14.5), work (16.8), neighborhoods (18.7), or family (24.3). The Internet is also far less segregated than networks of trusted friends (30.3) and political discussants (39.4).
Using our microdata sample, we estimate online segregation back to 2004 and find no evidence that the Internet is becoming more segregated over time.”
#Laura Silver, Christine Huang. Social media users more likely to interact with people who are different from them. 2019.
Quote: “Social media and messaging app users are more likely to encounter people who are different from them across all the categories we queried – whether income, political party, religious views or ethnicity.”
– Being physically close made you familiar and created similarities that bridged the gap of different world views so you didn’t murder each other. And your world view was probably not that different in the first place because it was formed by the same local culture.
Our tendency to favor those similar to us is at the root of many cognitive biases that shaped human interaction throughout history. Only in the early 20th century, political scientist William Sumner first identified that we are more likely to treat people that we identify as part of our group better than who is outside our group. In the 1970s social psychologist Henri Tajfel developed the social identity theory which explains why we group people into ‘them’ and ‘us’ categories.
#Decision Lab. The Similar-To-Me Effect. Retrieved October 2023.
https://thedecisionlab.com/reference-guide/psychology/the-similar-to-me-effect
Quote: “The similar-to-me effect is a cognitive bias that explains our tendency to prefer people that look and think like us. We have an affinity towards all things familiar to us, which is why the similar-to-me effect is also known as the affinity bias. While it might seem harmless in principle to associate ourselves with familiar people, the similar-to-me effect can lead to unjust consequences when applied to hiring practices, workplace promotions, and tolerance towards otherness.”
– When our brains evolved, this was enough. Whoever was around, was similar to us. We liked what was similar to us – this kept us aligned enough to work together despite our differences.
This can partly be explained within the Social Identity Theory as mentioned above, simply put a person’s sense of self based on the group membership. Social identity theory states that we show favoritism towards people that are similar to us because similar people help us construct our own sense of self. Those people that we use to construct our sense of self become our ‘in’ group and we tend to align ourselves to these people. Social identity theory explains why we group people into ‘them’ and ‘us’ categories, which can lead to differential treatment. This also underlies the related concept, social categorization, which is the process of grouping individuals based upon various social information.
Tajfel et al., Social categorization and intergroup behaviour. 1971
https://onlinelibrary.wiley.com/doi/abs/10.1002/ejsp.2420010202
Quote: “The main finding, confirmed in all three experiments, is clear; in a situation devoid of the usual trappings of ingroup membership and of all the vagaries of interacting with an outgroup, the Ss still act in terms of their ingroup membership and of an intergroup categorization. Their actions are unambiguously directed at favouring the members of their ingroup as against the members of the outgroup. This happens despite the fact that an alternative strategy - acting in terms of the greatest common good - is clearly open to them at a relatively small cost of advantages that would accrue to members of the ingroup.”
#Saul Mcleod. Social Identity Theory In Psychology (Tajfel & Turner, 1979). 2023
https://www.simplypsychology.org/social-identity-theory.html
Quote: “Social Identity Theory, proposed by Henri Tajfel and John Turner in the 1970s, posits that individuals derive a portion of their self-concept from their membership in social groups.The theory seeks to explain the cognitive processes and social conditions underlying intergroup behaviors, especially those related to prejudice, bias, and discrimination.
Tajfel and Turner (1979) proposed that the groups (e.g., social class, family, football team, etc.) people belonged to were important sources of pride and self-esteem.”
#Rhodes and Baron. The Development of Social Categorization. 2019.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577394/
Quote: “Social categorization is a universal mechanism for making sense of a vast social world with roots in perceptual, conceptual, and social systems. These systems emerge strikingly early in life and undergo important developmental changes across childhood. The development of social categorization entails identifying which ways of classifying people are culturally meaningful, how these categories might be used to predict, explain, and evaluate the behavior of other people, and how one’s own identity relates to these systems of categorization and representation. Social categorization can help children simplify and understand their social environment but has detrimental consequences in the forms of stereotyping, prejudice, and discrimination.”
– If you want or not, your brain sorts people by world views and opinions, into teams. This is not simply tribalism, it goes further. Researchers have called this process social sorting.
When this sorting of various aspects of social life are aligned along a single social identity defined by a political party, this is called social-sorting. Tendencies like in-group favoritism or out-group animosity underlied by social categorization result in affective polarization when the sorting is done over partisanship. Affective polarization differs from ideological polarization, it refers to dislike and distrust of opposing partisans.
#Iyengar, Sood and Lelkes. Affect, Not Ideology. A Social Identity Perspective on Polarization. 2012.
Quote: “Is affective polarization simply a symptom of divergent movement in policy attitudes among both partisan supporters and party elites? The evidence suggests otherwise. First, if ideological disagreement has contributed to affective polarization, we should observe considerably sharper thermometer differences among sorted partisans, i.e., liberal Democrats and conservative Republicans. However, the differences in thermometer ratings among the sorted partisans are only modestly higher (see table A4 in the Online Appendix).”
#Petter Törnberg. How digital media drive affective polarization through partisan sorting. 2022.
https://www.pnas.org/doi/epdf/10.1073/pnas.2207159119
Quote: “When individuals interact in clusters, the result tends to be local convergence, resulting in a stable plural patchwork of cross-cutting conflicts. However, when interaction takes place across space, the tendency is for groups to converge along the lines of partisan identity. The result is the crystallization of conflicting identities and the intensification of polarization,driven by a process in which sorting begets sorting and polariza-tion begets polarization. These dynamics thus suggest a feedback loop between partisan sorting and affective polarization: sorting causes partisans to“dislike, even loathe”one another (15), in turn reducing their mutual social influence which further intensi-fies the process of sorting.”
#Lilliana Mason. A Cross-Cutting Calm: How Social Sorting Drives Affective Polarization. 2016.
https://academic.oup.com/poq/article/80/S1/351/2223236
Quote: “In recent decades, a particular type of partisan sorting has been occurring in the American electorate. American partisan identities have grown increasingly linked with a number of other specific social identities. These include religious (Layman 1997, 2001; Green et al. 2007), racial (Mangum 2013; Krupnikov and Piston 2014), and other political group identities, such as the Tea Party (Campbell and Putnam 2011). This convergence, or “sorting,” goes beyond the gradual alignment of party and issue positions described most recently and thoroughly by Levendusky (2009, 2010). When religious, racial, and other political movement identities grow increasingly linked to one party or the other, this phenomenon can be called “social sorting.”
Quote: “Because a highly aligned set of social identities increases an individual’s perceived differences between groups, the emotions that result from group conflict are likely to be heightened among well-sorted partisans. An experimental design in a national online survey manipulates political threats and reassurances, including a threat to a party and a threat to distinct policy goals. Issue positions are found to drive anger and enthusiasm in the presence of issue-based messages, but not all party-based messages. Partisan identity drives anger and enthusiasm in the presence of party-based threats and reassurances, but not all issue-based messages. Social sorting, however, drives anger and enthusiasm in response to all threats and reassurances, suggesting that well-sorted partisans are more reliably emotionally reactive to political messages. Finally, these results are driven not by the most-sorted partisans, but by the emotional dampening effect that occurs among those with the most cross-cutting identities. As social sorting increases in the American electorate, the cooler heads inspired by cross-cutting identities are likely to be taking up a smaller portion of the electorate.”
Though not unrelated, it is slightly different from tribalism.
#The European Center for Populism Studies. Dictionary Of Populism. Retrieved October, 2023.
https://www.populismstudies.org/Vocabulary/cultural-tribalism/
Quote: “Tribalism is a loyalty or preference to one’s own people. As well as culture, it can apply to politics and sport. Cultural tribalism refers to the subdivision of society in groups who come together by a shared or specific type of thinking or behavior. In popular culture, cultural tribalism may also refer to a way of thinking or behaving in which people are loyal to their social group above all else, or, derogatorily, a type of discrimination or animosity based upon group differences.
According to an article by Aimee Lew, the concept describes how, as a group of people with similar values, lifestyles and languages, people tend to favor their own ‘tribe’ above others. At a glance, tribalism doesn’t seem bad at all. Until someone is on the outside of the tribe. Moreover, George Packer argues in an article that despite tribes demand loyalty, and in return they confer the security of belonging. They’re badges of identity, not of thought. In a way, they make thinking unnecessary, because they do it for you, and may punish you if you try to do it for yourself.”
– And this makes it less likely that you will seriously consider their position or opinion in the future. If you hear bad things about them, your brain is much more likely to believe it uncritically.
This is more broadly related to a concept called outgroup animosity, which is one of the mechanisms feeding into affective polarization mentioned above.
#Iyengar and Westwood. Fear and Loathing across Party Lines: New Evidence on Group Polarization. 2014.
https://onlinelibrary.wiley.com/doi/abs/10.1111/ajps.12152
Quote: “When defined in terms of social identity and affect toward copartisans and opposing partisans, the polarization of the American electorate has dramatically increased. We document the scope and consequences of affective polarization of partisans using implicit, explicit, and behavioral indicators. Our evidence demonstrates that hostile feelings for the opposing party are ingrained or automatic in voters’ minds, and that affective polarization based on party is just as strong as polarization based on race. We further show that party cues exert powerful effects on nonpolitical judgments and behaviors. Partisans discriminate against opposing partisans, doing so to a degree that exceeds discrimination based on race. We note that the willingness of partisans to display open animus for opposing partisans can be attributed to the absence of norms governing the expression of negative sentiment and that increased partisan affect provides an incentive for elites to engage in confrontation rather than cooperation.”
#Iyengar, Sood and Lelkes. Affect, Not Ideology. A Social Identity Perspective on Polarization. 2012.
Quote: “In summary, our three indicators of affective polarization all demonstrate that partisans in America are increasingly divided. The sense of partisan identity is increasingly associated with a Manichean, “us against them” view of the political world. Democrats and Republicans harbor generally negative feelings toward their opponents. Stereotypes of party supporters have become increasingly differentiated; positive traits accrue to members of the in-party, while negative traits are ascribed to opponents. There is sufficient animosity to make partisan affiliation relevant to inter-personal relations. Today, American partisans are highly polarized in their feelings about each other.”
#Taber, Cann & Kucsova. The Motivated Processing of Political Arguments. 2009.
https://link.springer.com/article/10.1007/s11109-008-9075-8
Quote: “We report the results of an experiment designed to replicate and extend recent findings on motivated political reasoning. In particular, we are interested in disconfirmation biases—the tendency to counter-argue or discount information with which one disagrees—in the processing of political arguments on policy issues. Our experiment examines 8 issues, including some of local relevance and some of national relevance, and manipulates the presentation format of the policy arguments. We find strong support for our basic disconfirmation hypothesis: people seem unable to ignore their prior beliefs when processing arguments or evidence. We also find that this bias is moderated by political sophistication and strength of prior attitude. We do not find, however, that argument type matters, suggesting that motivated biases are quite robust to changes in argument format. Finally, we find strong support for the polarization of attitudes as a consequence of biased processing.”
– On the flipside, people who share your world view and are maybe even more similar to you than many people in your real life. Which makes your brain like them a lot and kind of hyper align with them. People who think like you are probably good people because you are a good person and whatever social group you belong to is good! So your brain is more likely to believe their opinions. If you hear bad things about them, your brain is much more likely to dismiss it uncritically.
This is broadly related to in-group bias as mentioned above, tendency of giving preferential treatment to mutual group members. This is so strong that it is observed even when people are assigned to random groups, which renders the membership essentially meaningless.
#Zachary Elwood. How social media divides us: Is the medium of social media the message? (long version). 2020.
https://apokerplayer.medium.com/how-social-media-divides-us-c8070e0847d4#608a
Quote: “Our tendency to polarize into us-versus-them camps can be seen as relying on some basic psychological tendencies we have as tribal, social creatures.
We view our own group as being made up of individuals with diverse views and personalities while we view the other group as a mass of single-minded creatures. The so-called out-group homogeneity effect describes this tendency to view an opponent group (the out-group) as more monolithic than it actually is.
Related to this: if members on our own side have faults, we tend to overlook them and make excuses for them, but we will harshly judge members of the out-group. This tendency is referred to as in-group favoritism, amongst other names.
[...]
To be clear: humans have a tendency to get into these group-vs-group dynamics naturally, without aid from any technology. But social media seems to be an efficient amplifier of these tendencies.”
– The engagement driven social internet makes it worse because it wants to keep you online as long as possible. And the most engaging emotion is, unfortunately: Anger. The more angry you get, the more likely you are to share and engage, and this leads to social media amplifying the most extreme and controversial opinions.
Unfortunately, we are more prone to get psychologically affected by negative emotions than the positive ones, which is known as negativity bias. We tend to pay more attention to negative input, be it news or posts.
#Baumeister et al. Bad Is Stronger Than Good. 2001.
https://assets.csom.umn.edu/assets/71516.pdf
Quote: “The greater power of bad events over good ones is found in everyday events, major life events (e.g., trauma), close relationship outcomes, social network patterns, interpersonal interactions, and learning processes. Bad emotions, bad parents, and bad feedback have more impact than good ones, and bad information is processed more thoroughly than good. The self is more motivated to avoid bad self-definitions than to pursue good ones. Bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones. Various explanations such as diagnosticity and salience help explain some findings, but the greater power of bad events is still found when such variables are controlled. Hardly any exceptions (indicating greater power of good) can be found. Taken together, these findings suggest that bad is stronger than good, as a general principle across a broad range of psychological phenomena.”
#Rui Fan, Jichang Zhao, Yan Chen, Ke Xu. Anger is More Influential Than Joy: Sentiment Correlation in Weibo. 2013.
https://arxiv.org/abs/1309.2402
Quote: “Recent years have witnessed the tremendous growth of the online social media. In China, Weibo, a Twitter-like service, has attracted more than 500 million users in less than four years. Connected by online social ties, different users influence each other emotionally. We find the correlation of anger among users is significantly higher than that of joy, which indicates that angry emotion could spread more quickly and broadly in the network. While the correlation of sadness is surprisingly low and highly fluctuated. Moreover, there is a stronger sentiment correlation between a pair of users if they share more interactions. And users with larger number of friends posses more significant sentiment influence to their neighborhoods. Our findings could provide insights for modeling sentiment influence and propagation in online social networks.”
Following study provides evidence that the posts about political opponents are way more likely to be shared on Facebook and Twitter. The effect is much stronger than other established predictors of social media sharing.
Rathje et al., Out-group animosity drives engagement on social media. 2021
https://www.pnas.org/doi/10.1073/pnas.2024292118
Quote: We investigated whether out-group animosity was particularly successful at generating engagement on two of the largest social media platforms: Facebook and Twitter. Analyzing posts from news media accounts and US congressional members (n = 2,730,215), we found that posts about the political out-group were shared or retweeted about twice as often as posts about the in-group.
Each individual term referring to the political out-group increased the odds of a social media post being shared by 67%. Out-group language consistently emerged as the strongest predictor of shares and retweets: the average effect size of out-group language was about 4.8 times as strong as that of negative affect language and about 6.7 times as strong as that of moral-emotional language—both established predictors of social media engagement. Language about the out-group was a very strong predictor of “angry” reactions (the most popular reactions across all datasets), and language about the in-group was a strong predictor of “love” reactions, reflecting in-group favoritism and out-group derogation. ”
– It optimises not only to show us disagreement, but the worst disagreement possible. And because your stupid brain is sorting people into teams, whatever the worst opinions are, it assigns the same opinions to everybody on the other team.
The following study collected official press releases and Facebook posts issued by members of the 114th Congress in the US between Jan. 1, 2015, and April 30, 2016. Following chart shows the amount and types of reactions from over 100,000 Facebook posts versus their content in the context of the level of disagreement they contain, and it shows that the posts with disagreements got the most engagement.
#Pew Research Center, Critical posts get more likes, comments, and shares than other posts. 2017.
https://www.pewresearch.org/politics/2017/02/23/partisan-conflict-and-congressional-outreach/
Anger obviously is not the only motive, moral emotional language is for example found to increase the rate of dissemination of moral and political ideas by 20%.
#Brady et al., How social learning amplifies moral outrage expression in online social networks. 2021.
https://www.science.org/doi/10.1126/sciadv.abe5641
Quote: “Across two observational studies analyzing the tweet histories of 7331 total users (12.7 million total tweets) and with two behavioral experiments (total N = 240), we investigated how reinforcement learning and norm learning shape moral outrage expressions on social media. Our findings revealed three key discoveries about moral outrage in the digital age. First, social feedback specific to moral outrage expression significantly predicts future outrage expressions, suggesting that reinforcement learning shapes users’ online outrage expressions. Second, moral outrage expressions are sensitive to expressive norms in users’ social networks, over and above users’ own preferences, suggesting that norm learning processes guide moral expressions online. Third, network-level norms of expression moderate the social reinforcement of outrage: In networks that are more ideologically extreme, where outrage expression is more common, users are less sensitive to social feedback when deciding whether to express outrage.”
#Berger & Milkman. What Makes Online Content Viral? 2012.
https://journals.sagepub.com/doi/10.1509/jmr.10.0353
Quote: “Why are certain pieces of online content (e.g., advertisements, videos, news articles) more viral than others? This article takes a psychological approach to understanding diffusion. Using a unique data set of all the New York Times articles published over a three-month period, the authors examine how emotion shapes virality. The results indicate that positive content is more viral than negative content, but the relationship between emotion and social transmission is more complex than valence alone. Virality is partially driven by physiological arousal. Content that evokes high-arousal positive (awe) or negative (anger or anxiety) emotions is more viral. Content that evokes low-arousal, or deactivating, emotions (e.g., sadness) is less viral. ”
– What is striking and new about the online polarisation is that all the aspects from our lives that make us individuals, our lifestyle choices, the comedians or shows we watch, our religion, sense of fashion and so on are condensed, making it seem that they are parts of opposing and mutually exclusive identities.
As all the other aspects of life are condensed into one dimension, there is an emerging perception of two opposing, homogenous, and mutually exclusive identities.
#McCoy, Rahman & Somer. Polarization and the Global Crisis of Democracy: Common Patterns, Dynamics, and Pernicious Consequences for Democratic Polities. 2018. https://doi.org/10.1177/0002764218759576
Quote: “Moving beyond the conventional conceptualization of polarization as ideological distance between political parties and candidates, we offer a conceptualization of polarization highlighting its inherently relational nature and its instrumental political use. Polarization is a process whereby the normal multiplicity of differences in a society increasingly align along a single dimension and people increasingly perceive and describe politics and society in terms of “Us” versus “Them.” The politics and discourse of opposition and the social–psychological intergroup conflict dynamics produced by this alignment are a main source of the risks polarization generates for democracy, although we recognize that it can also produce opportunities for democracy. We argue that contemporary examples of polarization follow a frequent pattern whereby polarization is activated when major groups in society mobilize politically to achieve fundamental changes in structures, institutions, and power relations.”
#Markus Prior. Media and Political Polarization. 2013.
https://www.annualreviews.org/doi/abs/10.1146/annurev-polisci-100711-135242
Quote: “Of the two possible processes that generate a closer match of party ID and issue positions, changes in issue positions—what Layman & Carsey (2002b) call “party-based issue conversion” and Levendusky (2009b) refers to as “party-driven sorting”—appear to be more common (Levendusky 2009a,b), especially when the issue is not particularly important to the individual (Carsey & Layman 2006). This finding squares with the strong accumulated evidence that party ID is highly stable (e.g., Converse & Markus 1979, Green et al. 2002) and powerfully organizes many other components of people’s belief systems, including their core values (Goren 2005) and beliefs about objective conditions such as the crime rate or the state of the economy (Bartels 2002).”
#Pew Research Center. Only about one-in-five Trump and Biden supporters say they share the same core American values and goals. 2020.
– This simplifies and distorts disagreements about how we should run society so much that it often seems as if the people on the other team are actively, willfully making the world worse. That they are almost evil, beyond convincing with rationality, facts or civil discussion. While you are of course on the correct team, it may be hard to process that you may seem like that to people on the other team.
Unfortunately, affective polarization has already shown to have detrimental effects on democracies across the world.
#McCoy and Press. What Happens When Democracies Become Perniciously Polarized? 2022
Quote: “To rectify this gap, we used the Varieties of Democracy (V-Dem) data set to take a close look at episodes of pernicious polarization around the world since 1950 and trace their relationships with levels of democracy.6 The findings are not encouraging. Severe polarization correlates with serious democratic decline: of the fifty-two instances where democracies reached pernicious levels of polarization, twenty-six—fully half of the cases—experienced a downgrading of their democratic rating.7 Only sixteen episodes were able to reduce polarization to below-pernicious levels, and the decline in polarization was only sustained in nine of those cases. Quite strikingly, the United States is the only advanced Western democracy to have faced such intense polarization for such an extended period. The United States is in uncharted and very dangerous territory.”
#Somer, M., & McCoy, J. Déjà vu? Polarization and Endangered Democracies in the 21st Century. 2018.
https://journals.sagepub.com/doi/full/10.1177/0002764218760371
Quote: “Nevertheless, the potential pernicious dynamics and consequences of severe political and societal polarization on democracy should be taken very seriously. Once it is set in motion, polarization has built-in dynamics to become self-propagating and spiral out of control (Somer, 2001). As we discuss below, and various contributions in this issue elaborate from different angles, it activates many discursive, organizational, and psychological dynamics and causal mechanisms that endanger coexistence and the proper functioning of democratic systems. Within organizations ranging from political parties to the media and academia, polarization disadvantages social and political actors who shun polarizing and exclusionary discourse and uphold cross-cutting attachments, power sharing, and consensus seeking. Instead, it advantages actors willing and able to employ unyielding, exclusionary, and demagogic politics and rhetoric. It facilitates the development of rigid and antagonistic political identities. Hence, even when contributing to democratization in the short run, polarization can undermine the long-term structural, institutional, and psychological factors that build and sustain democracy.”
– This is especially bad in the US, where the two party system makes it extra easy to think of people in terms of teams – negative opinion about the other party has reached record highs.
Unfortunately, two-party system makes it easier to collapse all the other differences in life-style and values along a single division that deepens the partisan divide beyond the ideological differences.
#Boxell, Gentzkow and Shapiro. Cross-Country Trends in Affective Polarization. 2021.
https://www.nber.org/papers/w26669
Quote: “We measure trends in affective polarization in twelve OECD countries over the past four decades. According to our baseline estimates, the US experienced the largest increase in polarization over this period. Five countries experienced a smaller increase in polarization. Six countries experienced a decrease in polarization. We relate trends in polarization to trends in potential explanatory factors.”
A commentary on the above paper for a shorter read:
#U.S. is polarizing faster than other democracies, study finds. 2020.
https://www.brown.edu/news/2020-01-21/polarization
Quote: “In the study, Shapiro and colleagues present the first ever multi-nation evidence on long-term trends in “affective polarization” — a phenomenon in which citizens feel more negatively toward other political parties than toward their own. They found that in the U.S., affective polarization has increased more dramatically since the late 1970s than in the eight other countries they examined — the U.K., Canada, Australia, New Zealand, Germany, Switzerland, Norway and Sweden.
“A lot of analysis on polarization is focused on the U.S., so we thought it could be interesting to put the U.S. in context and see whether it is part of a global trend or whether it looks more exceptional,” Shapiro said. “We found that the trend in the U.S. is indeed exceptional.””
#Pew Research. As Partisan Hostility Grows, Signs of Frustration With the Two-Party System. 2022.
Quote: “Deeply negative views of the opposing party are far more widespread than in the past. About six-in ten Republicans (62%) and more than half of Democrats (54%) have a very unfavorable view of the other party in Pew Research Center surveys conducted this year. While these highly negative views of the opposing party are little changed in the last few years, the share expressing this level of antipathy is higher than it was even five years ago, and considerably higher than it was a few decades ago. In 1994, fewer than a quarter in both parties rated the other party very unfavorably.”
#Fletcher, R., Cornia, A., & Nielsen, R. K. (2020). How Polarized Are Online and Offline News Audiences? A Comparative Analysis of Twelve Countries. https://doi.org/10.1177/1940161219892768
Quote: “We develop a way of measuring how polarized news audiences are at the national level. Then, we analyse survey data from 12 countries and find: (i) that cross-platform (online and offline) news audience polarization is highest in the USA, and within Europe, higher in polarized pluralist/southern countries than in democratic corporatist countries. Furthermore, (ii) in most countries online news audience polarization is higher than offline, but in a small number it’s lower. Taken together our findings highlight that, despite the well-documented fears associated with algorithmic selection, news audience polarization is not inevitable in environments that are increasingly characterised by digital news consumption, and that the
historical, economic and political factors emphasised by the comparative tradition remain critically important for our understanding of global trends.”
#Iyengar et al. The Origins and Consequences of Affective Polarization in the United States. 2019.
https://pcl.sites.stanford.edu/sites/g/files/sbiybj22066/files/media/file/iyengar-ar-origins.pdf
Quote: “Several features of the contemporary environment have exacerbated partisans’ proclivity to divide the world into a liked in group (one’s own party) and a disliked out group (the opposing party). First, in the last 50 years, the percentage of sorted partisans, i.e., partisans who identify with the party most closely reflecting their ideology, has steadily increased (Levendusky 2009). When most Democrats are liberals and most Republicans are conservatives, copartisans are less likely to encounter conflicting political ideas and identities (Roccas & Brewer 2002) and are more likely to see nonidentifiers as socially distant. Sorting likely leads people to perceive both opposing partisans and copartisans as more extreme than they really are, with misperceptions about opposing partisans being more acute (Levendusky & Malhotra 2016b). ”
– These communities worked because they mirrored real life much more than social media: Each village had its own culture and set of rules. Maybe one community was into rough humour and soft moderation, another had strict rules to be emphatic and banned easily. If you didn’t play by the village rules, you would be banned – or you could just go and move to another village that fit you better.
Though there is no direct research comparing the old internet to the new internet in this context, the following study indirectly suggests that a community with some control over the algorithm of the platform shows a visible difference than the one that lacks it.
#Cinelli et al., The echo chamber effect on social media. 2020.
Quote: “However, a direct comparison of news consumption on Facebook and Reddit shows higher segregation on Facebook. Furthermore, we find significant differences across platforms in terms of homophilic patterns in the network structure and biases in the information diffusion toward like-minded users. A clearcut distinction emerges between social media having a feed algorithm tweakable by the users (e.g., Reddit) and social media that don’t provide such an option (e.g., Facebook and Twitter).”
– So instead of all of us gathering at once place, overwhelming our brains at a town square that in the end just leads to us going insane, one solution for less social sorting may be extremely simple: go back to smaller online communities.
#Brian X. Chen. The Future of Social Media Is a Lot Less Social. 2023.
https://www.nytimes.com/2023/04/19/technology/personaltech/tiktok-twitter-facebook-social.html
Quote: “The change has implications for large social networking companies and how people interact with one another digitally. But it also raises questions about a core idea: the online platform. For years, the notion of a platform — an all-in-one, public-facing site where people spent most of their time — reigned supreme. But as big social networks made connecting people with brands a priority over connecting them with other people, some users have started seeking community-oriented sites and apps devoted to specific hobbies and issues.
“Platforms as we knew them are over,” said Zizi Papacharissi, a communications professor at the University of Illinois-Chicago, who teaches courses on social media. “They have outlived their utility.”
The shift helps explain why some social networking companies, which continue to have billions of users and pull in billions of dollars in revenue, are now exploring new avenues of business. Twitter, which is owned by Elon Musk, has been pushing people and brands to pay $8 to $1,000 a month to become subscribers. Meta, the parent company of Facebook and Instagram, is moving into the immersive online world of the so-called metaverse.”
#Chand Rajendra-Nicolucci, Michael Sugarman, and Ethan Zuckerman. The Three Legged Stool: A Manifesto for a Smaller, Denser Internet. 2023.
https://publicinfrastructure.org/2023/03/29/the-three-legged-stool/
Quote: “At the Initiative for Digital Public Infrastructure, we believe that a truly sustainable and resilient digital public sphere is possible and is actively being created. We envision a public sphere supported by these three legs:
– Consists of many different platforms with a wide variety of scales and purposes;
– Users can navigate with a loyal client that aggregates, cross-posts, and curates;
– Is all supported by cross-cutting services rooted in interoperable data.
In this paper, we illustrate our vision for a healthier digital public sphere by exploring what we believe are its three constitutive parts.”