Socioeconomic Networks and Network Science Workshop

15:05-15:55 Giacomo Livan

"Leveraging academic networks to understand scientific impact"

Scientific impact is a multifaceted concept, and a notoriously hard one to quantify. Yet, it is increasingly operationalized in terms of the citations received by research papers and of citation-based bibliometric indicators, such as the h-index and the impact factor. Despite quite a lot of controversy, citations and bibliometric indicators nowadays inform all aspects of academic decision-making, from tenure decisions to grant attributions. It is therefore of paramount importance to determine what factors may influence such indicators. In this talk, I will show how different academic networks can contribute to explain citation patterns and the evolution of bibliometric indicators. Namely, I will show how reciprocity in citation author networks has steadily increased for decades, reflecting the increasing pressure that researchers have faced to attract higher citation numbers. I will also present similar evidence of coordination phenomena at the level of journals. Finally, I will show how long-term sustained scientific impact can sometimes be traced back to the early career proximity to top scientists. I will present evidence that junior researchers who coauthor just one paper with the top-cited scientists in their field enjoy a permanent competitive advantage with respect to their peers throughout the rest of their careers. I will conclude by discussing how these findings should encourage a critical and nuanced approach to the use of bibliometric indicators.

16:10-16:45 Petter Holme

"Freedom of choice adds value to public goods"

Public goods, ranging from judiciary to sanitation to parkland, permeate daily life. They have been a subject of intense interdisciplinary study, with a traditional focus being on participation levels in isolated public goods games (PGGs) as opposed to a more recent focus on participation in PGGs embedded into complex social networks. We merged the two perspectives by arranging voluntary participants into one of three network configurations, upon which volunteers played a number of iterated PGGs within their network neighborhood. The purpose was to test whether the topology of social networks or a freedom to express preferences for some local public goods over others affect participation. The results show that changes in social networks are of little consequence, yet volunteers significantly increase participation when they freely express preferences. Surprisingly, the increase in participation happens from the very beginning of the game experiment, before any information about how others play can be gathered. Such information does get used later in the game as volunteers seek to correlate contributions with higher returns, thus adding significant value to public goods overall. These results are ascribable to a small number of behavioral phenotypes, and suggest that societies may be better off with bottom-up schemes for public goods provision.

10:05-10:40 Junming Huang

"Historical comparison of gender inequality in scientific careers across countries and disciplines"

There is extensive, yet fragmented, evidence of gender differences in academia suggesting that women are underrepresented in most scientific disciplines and publish fewer articles throughout a career, and their work acquires fewer citations. Here, we offer a comprehensive picture of longitudinal gender differences in performance through a bibliometric analysis of academic publishing careers by reconstructing the complete publication history of over 1.5 million gender-identified authors whose publishing career ended between 1955 and 2010, covering 83 countries and 13 disciplines. We find that, paradoxically, the increase of participation of women in science over the past 60 years was accompanied by an increase of gender differences in both productivity and impact. Most surprisingly, though, we uncover two gender invariants, finding that men and women publish at a comparable annual rate and have equivalent career-wise impact for the same size body of work. Finally, we demonstrate that differences in publishing career lengths and dropout rates explain a large portion of the reported career-wise differences in productivity and impact, although productivity differences still remain. This comprehensive picture of gender inequality in academia can help rephrase the conversation around the sustainability of women’s careers in academia, with important consequences for institutions and policy makers.

11:45-12:20 Yunkyu Sohn

"A Brief Introduction to the Practices of Empirical Social Science"

Any academic discipline is constrained by particular disciplinary norms which determine topical significance and the criteria of validity. Despite the fact that each discipline has been well isolated with each other for a long time, the surge of interdisciplinary research, due to lowered barriers for the access to data sets from various domains, calls our attention to the differences in the criteria of evaluating the importance and validity of scientific arguments between different disciplines.

By citing standard curricular in social science, this talk introduces the central tenet of contemporary social science, empirical verification of theoretical claims, and its practices to computational social scientists with natural science backgrounds. From research design perspectives, I argue that successful contributions would be possible when natural scientists are aware of the canonical empirical verification (statistical modeling) strategies and the conventions of using empirical evidence in social science. By using network science as an example, I provide a constructive proposal for how approaches and methods in physics and related disciplines can be used to make impacts under the paradigmatic norms of contemporary social science.

14:20-14:55 Mengqiao Xu

"Modular gateway-ness connectivity and structural core organization in maritime network science"

Around 80% of global trade by volume is transported by sea, and thus the maritime transportation system is fundamental to the world economy. To better exploit new international shipping routes, we need to understand the current ones and their complex systems association with international trade. We investigate the structure of the global liner shipping network (GLSN), finding it is an economic small-world network with a trade-off between high transportation efficiency and low wiring cost. To enhance understanding of this trade-off, we examine the modular segregation of the GLSN; we study provincial-, connector-hub ports and propose the definition of gateway-hub ports, using three respective structural measures. The gateway-hub structural-core organization seems a salient property of the GLSN, which proves importantly associated to network integration and function in realizing the cargo transportation of international trade. This finding offers new insights into the GLSN’s structural organization complexity and its relevance to international trade.

15:10-16:00 Manuel Sebastian Mariani

"Predicting collective success from individual behavior"

Can we predict top-performing products, services, or businesses by monitoring the behavior of a small set of individuals? While long-standing theories in social sciences and innovation diffusion have suggested that there exists a minority of individuals (often termed as "opinion leaders", "influencers") who can accelerate the diffusion of innovations, the answer to this question remains debated. Motivated by this question, we analyze a large-scale anonymized dataset that includes credit-card transactions in brick-and-mortar stores across an entire nation, and a call-data record from the same nation. Surprisingly, we find that the purchasing history alone enables the detection of small sets of individuals - called discoverers - whose early purchases are consistently predictive of success for the visited store. In contrast with the assumptions by most existing studies on word-of-mouth processes, social hubs selected by network centrality (detected from the call-data record) are not consistently predictive of success. We find similar results when attempting to predict the future success of user-generated content in an online community, and we provide preliminary insights on potential traits that might explain the discoverers' predictive power. Our findings indicate that companies and organizations can detect the discoverers directly from the purchase or content adoption data, without the need for social network data.