Political polarization seems to be rising at an alarming rate in the United States. Those on opposite sides of the political spectrum are increasingly viewing each other more negatively, with this effect amplified in the rhetoric of elected officials. In this research, I examine social media posts from Democratic representatives on Bluesky, a growing social media platform with a mostly liberal user base. I collect a novel dataset directly from Bluesky and construct several independent variables. These include 4 distinct measures of polarization (positivity, affective polarization, issue polarization, and cross-party mentions), an indicator for house membership, and 4 indicators for salient policy-related content (science, economic, healthcare, and governance). I model the predicted effect of each variable on like-count and reply-count while controlling for the number of account followers. Results indicate that 3 of the 4 polarization variables significantly predict an increase in engagement. House membership significantly predicts less engagement. Finally, I find mixed results for the policy-related variables, leading to a discussion about future research on user engagement. These results show that the engaging effect of polarizing speech, found in previous literature, is robust even on a partisan platform without users from the other side of the aisle.
","abstract_html":"<p>Political polarization seems to be rising at an alarming rate in the United States. Those on opposite sides of the political spectrum are increasingly viewing each other more negatively, with this effect amplified in the rhetoric of elected officials. In this research, I examine social media posts from Democratic representatives on Bluesky, a growing social media platform with a mostly liberal user base. I collect a novel dataset directly from Bluesky and construct several independent variables. These include 4 distinct measures of polarization (positivity, affective polarization, issue polarization, and cross-party mentions), an indicator for house membership, and 4 indicators for salient policy-related content (science, economic, healthcare, and governance). I model the predicted effect of each variable on like-count and reply-count while controlling for the number of account followers. Results indicate that 3 of the 4 polarization variables significantly predict an increase in engagement. House membership significantly predicts less engagement. Finally, I find mixed results for the policy-related variables, leading to a discussion about future research on user engagement. These results show that the engaging effect of polarizing speech, found in previous literature, is robust even on a partisan platform without users from the other side of the aisle.</p>","abstract_has_math":false,"creators":["Derr, Brandon"],"institution":null,"degree_name":"Master of Arts (MA)","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Iliyan Iliev","Marek Steedman","Joseph Weinberg"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12-01T08:00:00Z","date_published":"2025-12-01T08:00:00Z","updated_at":"2026-07-24T05:45:55Z","subjects":["social media","polarization","Bluesky","Congress","American Politics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://aquila.usm.edu/masters_theses/1159","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Iliyan Iliev","Marek Steedman","Joseph Weinberg"]},{"key":"dc:creator","label":"Author","values":["Derr, Brandon"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2028-08-24T07:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Arts (MA)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["social media","polarization","Bluesky","Congress","American Politics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://aquila.usm.edu/masters_theses/1159"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Political polarization seems to be rising at an alarming rate in the United States. Those on opposite sides of the political spectrum are increasingly viewing each other more negatively, with this effect amplified in the rhetoric of elected officials. In this research, I examine social media posts from Democratic representatives on Bluesky, a growing social media platform with a mostly liberal user base. I collect a novel dataset directly from Bluesky and construct several independent variables. These include 4 distinct measures of polarization (positivity, affective polarization, issue polarization, and cross-party mentions), an indicator for house membership, and 4 indicators for salient policy-related content (science, economic, healthcare, and governance). I model the predicted effect of each variable on like-count and reply-count while controlling for the number of account followers. Results indicate that 3 of the 4 polarization variables significantly predict an increase in engagement. House membership significantly predicts less engagement. Finally, I find mixed results for the policy-related variables, leading to a discussion about future research on user engagement. These results show that the engaging effect of polarizing speech, found in previous literature, is robust even on a partisan platform without users from the other side of the aisle.
"]},{"key":"dc:title","label":"Title","values":["Polarized Without the Other Side: Measurements from Congress on Bluesky"]}]}],"canonical_facts":{"dc:contributor":["Iliyan Iliev","Marek Steedman","Joseph Weinberg"],"dc:creator":["Derr, Brandon"],"dc:date.available":["2028-08-24T07:00:00Z"],"dc:description.abstract":["Political polarization seems to be rising at an alarming rate in the United States. Those on opposite sides of the political spectrum are increasingly viewing each other more negatively, with this effect amplified in the rhetoric of elected officials. In this research, I examine social media posts from Democratic representatives on Bluesky, a growing social media platform with a mostly liberal user base. I collect a novel dataset directly from Bluesky and construct several independent variables. These include 4 distinct measures of polarization (positivity, affective polarization, issue polarization, and cross-party mentions), an indicator for house membership, and 4 indicators for salient policy-related content (science, economic, healthcare, and governance). I model the predicted effect of each variable on like-count and reply-count while controlling for the number of account followers. Results indicate that 3 of the 4 polarization variables significantly predict an increase in engagement. House membership significantly predicts less engagement. Finally, I find mixed results for the policy-related variables, leading to a discussion about future research on user engagement. These results show that the engaging effect of polarizing speech, found in previous literature, is robust even on a partisan platform without users from the other side of the aisle.
"],"dc:identifier":["https://aquila.usm.edu/masters_theses/1159"],"dc:subject":["social media","polarization","Bluesky","Congress","American Politics"],"dc:title":["Polarized Without the Other Side: Measurements from Congress on Bluesky"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["Master of Arts (MA)"]},"updated_at":"2026-07-24T05:45:55Z"}