Modeling and Predicting News Consumption on Twitter

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Author(s)
Uri
Date Issued
11 July 2018
Date Available
10T11:52:19Z July 2019
Abstract
Relatively little is known about the news consumption amongst social media users, despite the proliferation of news sharing, distribution platforms and news aggregators. In this paper, we present the Twitter News Model (TNM), a computational data-driven approach to elucidate the dynamics of news consumption on Twitter. We apply the TNM to a dataset of interactions between users and journalists/ newspapers to reveal what drives users’ consumption of news on Twitter, and predictively relate users’ news beliefs, motivations, and attitudes to their consumption of news.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Conference Publication
Publisher
ACM
Start Page
321
End Page
329
Copyright (Published Version)
2018 the Authors
Keywords
DOI
Web versions
Language
English
Status of Item
Peer reviewed
Part of
UMAP '18 Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization
Description
UMAP 2018: User Modeling, Adaptation and Personalization, Nanyang Technological University, Singapore, July 8-11 2018
ISBN
978-1-4503-5589-6
This item is made available under a Creative Commons License
Owning collection
Insight Research Collection