Demographics of news sharing in the U.S. twittersphere

Julio C.S. Reis, Haewoon Kwak, Jisun An, Johnnatan Messias, Fabrício Benevenuto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationHT 2017 - Proceedings of the 28th ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery, Inc
Pages195-204
Number of pages10
ISBN (Electronic)9781450347082
DOIs
Publication statusPublished - 4 Jul 2017
Event28th ACM Conference on Hypertext and Social Media, HT 2017 - Prague, Czech Republic
Duration: 4 Jul 20177 Jul 2017

Other

Other28th ACM Conference on Hypertext and Social Media, HT 2017
CountryCzech Republic
CityPrague
Period4/7/177/7/17

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Keywords

  • Demographics
  • News Sharing
  • Online News
  • Social Media
  • Twitter

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence
  • Human-Computer Interaction
  • Software

Cite this

Reis, J. C. S., Kwak, H., An, J., Messias, J., & Benevenuto, F. (2017). Demographics of news sharing in the U.S. twittersphere. In HT 2017 - Proceedings of the 28th ACM Conference on Hypertext and Social Media (pp. 195-204). Association for Computing Machinery, Inc. https://doi.org/10.1145/3078714.3078734