Abstract: 

Social media algorithms have a deep influence on everyday life, and not everyone is aware of the effects that they create. One such effect is their tendency to create echo chambers where little to no information that challenges a user’s beliefs is introduced. Most studies researching this phenomenon focus on accounts within these echo chambers and how often they are recommended. A large gap in this process is that these methods do not represent how users may interact with their social media feeds directly by “like”-ing specific posts. Using American bipartisan politics to investigate echo chambers, this study intends to reveal the polarization of the platforms 𝕏 and Bluesky when matched with a left or right political bias. A quasi-experimental method using one left-leaning group, one right-leaning group, and one neutral group per platform was used. The occurrence of posts with aligned bias in the experimental accounts was compared to that of the neutral accounts to determine whether exposure was polarized or dispersed. Results concluded that an echo chamber was created for all experimental accounts, with the right-leaning account showing more polarization than the left-leaning account on 𝕏. For Bluesky however, a stronger echo chamber was found on all accounts due to a high left-leaning bias on the platform. 𝕏 and Bluesky users can use this information to employ more caution when considering the information they receive to be factual or non-partisan. To help prevent the spread of misinformation online, media literacy and ethics must be taught in schools.

Keywords: Social media, algorithms, selective exposure, echo chamber, filter bubble, polarization