JOURNAL ARTICLE
The Role of Online and Geographically Distant Social Networks in Political Decision-Making: Empirical Evidence from the 2016 United States Presidential Election.
Published In: Journal of the Association for Information Systems, 2024, v. 25, n. 3. P. 721 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Basak, Ecem; Tafti, Ali; Min-Seok Pang 3 of 3
Abstract
Social ties play a prominent role in individuals' political decision-making. They influence partisan defections, political participation, voting decisions, and political information acquisition. Much of the literature focuses on personal social networks or geographically close networks. Yet one's social network might also include acquaintances or other connections in more distant places that are maintained via online networks. In this study, we exploit Facebook's Social Connectedness Index, which reflects social connections across the United States, and we investigate the role of social connectedness in political decision-making among individuals who are located across distant geographical regions. Our results suggest that social connectedness between counties has a homogenizing effect on voting for the same presidential candidate, either Democratic or Republican. On the other hand, social connectedness is likely to have a differentiating effect on voting for an independent or a third-party candidate. Moreover, this effect is moderated by the socioeconomic characteristics of the counties, such as education, race, population density, household income, industry, and gender composition. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of the Association for Information Systems. 2024/05, Vol. 25, Issue 3, p721
- Document Type:Article
- Subject Area:Political Science
- Publication Date:2024
- ISSN:1536-9323
- DOI:10.17705/1jais.00851
- Accession Number:177097666
- Copyright Statement:Copyright of Journal of the Association for Information Systems is the property of Association for Information Systems and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.