Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/32861
Title: Algorithmic Curation and Users’ Civic Attitudes: A Study on Facebook News Feed Results
Authors: Papa, Venetia 
Photiadis, Thomas 
Major Field of Science: Social Sciences
Field Category: Media and Communications
Keywords: Social media;Civic participation;Algorithmic curation;Incidental exposure;Customization
Issue Date: 15-Sep-2021
Source: Information, 2021, vol.12, no.12, 522
Volume: 12
Issue: 12
Start page: 522
Journal: Information 
Abstract: Facebook users are exposed to diverse news and political content; this means that Facebook is a significant tool for the enhancement of civic participation and engagement in politics. However, it has been argued that Facebook, through its algorithmic curation reinforces the pre-existing attitudes of individuals, rather than challenging or potentially altering them. The objective of this study is to elucidate the emotional and behavioural impact of the personalization of Facebook users’ News Feeds results, and thereby to uncover a possible link between their online and offline civic attitudes. Firstly, we investigate the extent to which users’ Facebook News Feeds results are personalized and customized to fit users’ pre-existing civic attitudes and political interests. Secondly, we explore whether users embody new roles as a result of their emotional and behavioural interaction with political content on Facebook. Our methodology is based on a quantitative survey involving 108 participants. Our findings indicate that, while Facebook can potentially expose users to varying political views and beliefs, it tends to reinforce existing civic attitudes and validate what users already hold to be true. Furthermore, we find that users themselves often assume a proactive stance towards Facebook News Feed results, acquiring roles in which they filter and even censor the content to which they are exposed and thus trying to obfuscate algorithmic curation.
URI: https://hdl.handle.net/20.500.14279/32861
ISSN: 2078-2489
DOI: 10.3390/info12120522
Rights: Attribution 4.0 International
Type: Article
Affiliation : University of Cyprus 
DatAct Lab 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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