Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/22790
Title: Investigating Users’ Perceived Credibility of Real and Fake News Posts in Facebook’s News Feed: UK Case Study
Authors: Bates, Neil 
Sousa, Sonia C. 
Major Field of Science: Social Sciences
Field Category: Media and Communications
Keywords: Brexit;Credibility;Facebook;Fake new;Human factors;News feed;Tabloids;United Kingdom
Issue Date: 2021
Source: AHFE Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, 2020, 16-20 July, USA
Conference: AHFE: International Conference on Applied Human Factors and Ergonomics 
Abstract: The purpose of this research was to understand differences in UK users’ perceived credibility of real and fake news posts in Facebook’s news feed based on location, age, gender, education level, frequency of Facebook use, and intention to interact. A survey was designed to collect and measure demographic data from UK-based Facebook users, their behaviors, and perceived credibility of real and fake news posts. The study has made it evident that the perceived credibility of a Facebook post is dependent on the post origin and its truthfulness. The study also points to an interesting phenomenon that users are more likely to interact with posts that are seen as more credible.
URI: https://hdl.handle.net/20.500.14279/22790
ISBN: 978-3-030-51328-3
DOI: 10.1007/978-3-030-51328-3_25
Rights: © The Editor(s) (if applicable) and The Author(s)
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation : Cyprus University of Technology 
Tallinn University 
Publication Type: Peer Reviewed
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

CORE Recommender
Show full item record

SCOPUSTM   
Citations 50

2
checked on Mar 14, 2024

Page view(s)

306
Last Week
0
Last month
5
checked on Dec 3, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons