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Opinion Formation of Partisan Media Users in the Changing Media Environment- [electronic resource]

자료유형: 학위논문파일 국외

최종처리일시: 20240214101924

ISBN: 9798380859592

DDC: 320

저자명: Yan, Yaojun.

서명/저자: Opinion Formation of Partisan Media Users in the Changing Media Environment - [electronic resource]

발행사항: [S.l.]: : Indiana University., 2023

발행사항: Ann Arbor : : ProQuest Dissertations & Theses,, 2023

형태사항: 1 online resource(147 p.)

주기사항: Source: Dissertations Abstracts International, Volume: 85-05, Section: B.

주기사항: Advisor: Shanahan, James;Menczer, Filippo.

학위논문주기: Thesis (Ph.D.)--Indiana University, 2023.

사용제한주기: This item must not be sold to any third party vendors.

초록/해제: 요약In the first quarter of the 21st century, widening political polarization has been deemed poisonous to a healthy deliberative democracy. Concomitantly, changing media systems, powered by high-speed internet, social media, and computational automation, have been revolutionizing every aspect of our lives, in particular the process by which we receive, retain, and react to political opinions. The relationships between the media environment and the formation of political opinion have become unprecedentedly complex. This dissertation aims to further unravel this complexity by studying political bots, misinformation during the 2020 US Presidential Election, and the effects of a high-choice media environment on opinion formation.The first study uses an online experiment to test how the partisanship of participants predicts their mislabeling of political bots with different partisan personas as real human users. Results show asymmetrical biases: Democrats are more likely to confuse Republican users as bots while Republicans are more likely to mislabel Republican bots as real humans. Not only do the findings confirm the theory of motivated reasoning, but the activation of partisan biases during bot recognition also showcases how encountering automated political manipulation can increase suspicion toward the opposite party.The second study is a six-wave national-demographic representative tracking survey that shows how belief in false narratives during the 2020 US Presidential Election connects to partisanship and political ideology. The results show that while partisanship alone significantly predicts susceptibility to false information, political engagement through social media during the presidential campaign further consolidates the connections between the two.The third study uses an agent-based model to test how unified and divergent mass media systems with different audience reach can affect public opinion dynamics. The results provide a formal theoretical framework accounting for competing evidence regarding the effects of a high-choice environment on political polarization.Each study focuses on a different level of analysis in the complex media system. The first centers around the consequences of cross-sectional user-message interactions at the individual level; the second investigates polarization and its consequences at a societal level; and the last uses computational simulation to explore seemingly competing classic media effects theories -cultivation theory vs. selective exposure- within a meta-theoretical model. This dissertation showcases how evolving media systems can reinforce partisan identities by not only altering the presentation of partisan media content but also the behavioral engagement with and the cognitive processing of political information.