short-paper

Demographics of News Sharing in the U.S. Twittersphere

Authors:

Julio C.S. Reis,

Johnnatan Messias,

Fabrício BenevenutoAuthors Info & Claims

HT '17: Proceedings of the 28th ACM Conference on Hypertext and Social Media

Pages 195 - 204

https://doi.org/10.1145/3078714.3078734

Published: 04 July 2017 Publication History

Abstract

The widespread adoption and dissemination of online news through social media systems have been revolutionizing many segments of our society and ultimately our daily lives. In these systems, users can play a central role as they share content to their friends. Despite that, little is known about news spreaders in social media. In this paper, we provide the first of its kind in-depth characterization of news spreaders in social media. In particular, we investigate their demographics, what kind of content they share, and the audience they reach. Among our main findings, we show that males and white users tend to be more active in terms of sharing news, biasing the news audience to the interests of these demographic groups. Our results also quantify differences in interests of news sharing across demographics, which has implications for personalized news digests.

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Cited By

O'Connor KGolder SWeissenbacher DKlein AMagge AGonzalez-Hernandez G(2024)Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping ReviewJournal of Medical Internet Research10.2196/4792326(e47923)Online publication date: 15-Mar-2024
https://doi.org/10.2196/47923
Joy APathak RShrestha ASpezzano FWiniecki D(2024)Modeling the Diffusion of Fake and Real News through the Lens of the Diffusion of Innovations TheoryACM Transactions on Social Computing10.1145/36748827:1-4(1-24)Online publication date: 20-Jul-2024
https://dl.acm.org/doi/10.1145/3674882
Ahmed KKhan MHaq IMazroa AM.S. SInnab NAlajmi MAlkahtani H(2024)Social media’s dark secrets: A propagation, lexical and psycholinguistic oriented deep learning approach for fake news proliferationExpert Systems with Applications10.1016/j.eswa.2024.124650255(124650)Online publication date: Dec-2024
https://doi.org/10.1016/j.eswa.2024.124650
Show More Cited By

Index Terms

Demographics of News Sharing in the U.S. Twittersphere
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology
2. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social media

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Information & Contributors

Information

Published In

cover image ACM Conferences

HT '17: Proceedings of the 28th ACM Conference on Hypertext and Social Media

July 2017

336 pages

ISBN:9781450347082

DOI:10.1145/3078714

General Chairs:
Peter Dolog
Aalborg University, Denmark
,
Peter Vojtas
Charles University, Prague, Czech Republic
,
Program Chairs:
Francesco Bonchi
ISI Foundation, Turin, Italy
,
Denis Helic
Graz University of Technology, Austria

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

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Published: 04 July 2017

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FAPEMIG-PRONEX-MASWeb Models Algorithms and Systems for the Web

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HT'17

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SIGWEB

HT'17: 28th Conference on Hypertext and Social Media

July 4 - 7, 2017

Prague, Czech Republic

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HT '17 Paper Acceptance Rate 19 of 69 submissions, 28%;

Overall Acceptance Rate 378 of 1,158 submissions, 33%

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Cited By

O'Connor KGolder SWeissenbacher DKlein AMagge AGonzalez-Hernandez G(2024)Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping ReviewJournal of Medical Internet Research10.2196/4792326(e47923)Online publication date: 15-Mar-2024
https://doi.org/10.2196/47923
Joy APathak RShrestha ASpezzano FWiniecki D(2024)Modeling the Diffusion of Fake and Real News through the Lens of the Diffusion of Innovations TheoryACM Transactions on Social Computing10.1145/36748827:1-4(1-24)Online publication date: 20-Jul-2024
https://dl.acm.org/doi/10.1145/3674882
Ahmed KKhan MHaq IMazroa AM.S. SInnab NAlajmi MAlkahtani H(2024)Social media’s dark secrets: A propagation, lexical and psycholinguistic oriented deep learning approach for fake news proliferationExpert Systems with Applications10.1016/j.eswa.2024.124650255(124650)Online publication date: Dec-2024
https://doi.org/10.1016/j.eswa.2024.124650
Wang LRzeszotarski J(2023)Understanding Motivational Factors in Social Media News Sharing DecisionsProceedings of the ACM on Human-Computer Interaction10.1145/35795387:CSCW1(1-30)Online publication date: 16-Apr-2023
https://dl.acm.org/doi/10.1145/3579538
Sivayoganathan TKirpalani A(2023)Shaping Social Media: Is Twitter an Equitable tool for Professional Development?Journal of Medical Systems10.1007/s10916-023-02013-347:1Online publication date: 16-Nov-2023
https://doi.org/10.1007/s10916-023-02013-3
ÜNAL YŞENCAN İKURBANOĞLU S(2022)News Consumption and Sharing Behaviors of Undergraduate Students in Turkey in the Post-Truth EraTurk Kutuphaneciligi - Turkish Librarianship10.24146/tk.1081859Online publication date: 17-Aug-2022
https://doi.org/10.24146/tk.1081859
Golder SStevens RO'Connor KJames RGonzalez-Hernandez G(2022)Methods to Establish Race or Ethnicity of Twitter Users: Scoping ReviewJournal of Medical Internet Research10.2196/3578824:4(e35788)Online publication date: 29-Apr-2022
https://doi.org/10.2196/35788
Stiles ESwearingen CSeiter L(2022)Life of the Party: Social Networks, Public Attention, and the Importance of Shocks in the Presidential Nomination ProcessSocial Science Computer Review10.1177/0894439322107459941:4(1405-1419)Online publication date: 2-Mar-2022
https://doi.org/10.1177/08944393221074599
Peng YYang T(2021)Anatomy of audience duplication networks: How individual characteristics differentially contribute to fragmentation in news consumption and trustNew Media & Society10.1177/146144482199155924:10(2270-2290)Online publication date: 15-Feb-2021
https://doi.org/10.1177/1461444821991559
Karkkainen KJoo J(2021)FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation2021 IEEE Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV48630.2021.00159(1547-1557)Online publication date: Jan-2021
https://doi.org/10.1109/WACV48630.2021.00159
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