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Modeling and Predicting News Consumption on Twitter
Author(s)
Date Issued
2018-07-11
Date Available
2019-07-10T11:52:19Z
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
Web versions
Language
English
Status of Item
Peer reviewed
Journal
UMAP '18 Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization
Conference Details
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
File(s)
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Name
Modeling_and_Predicting_News_Consumption_on_Twitter__1_.pdf
Size
2.04 MB
Format
Adobe PDF
Checksum (MD5)
0bb6147a45e2ea0c99e3046c47697ff7
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