Community analysis of news article sharing on Twitter

Devipsita Bhattacharya, Sudha Ram

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

Microblogging platforms such as Twitter facilitate article sharing by news agencies for online news consumption. The broadcasting feature of Twitter allows news agencies to reach a large audience through news article tweets. Users on Twitter share these tweets and contribute to news article cascades. We analyzed the relationships formed between these Twitter users as they retweeted article(s) over a period of time. Based on a dataset of news article tweets and retweets collected over a period of two weeks, we extracted implicit networks created by user-article and user-user relationships. We found that although there is low article overlap within the retweeting audience, a small set of users connect via strong bonds and are very influential in news propagation. Our methodology for analyzing these networks provides important insights into the user communities participating in news article propagation. The results of our study have useful implications for news agencies to help them develop accurate article recommendations for their target audience and to design effective advertising and pricing strategies for their articles.

Original languageEnglish (US)
StatePublished - Jan 1 2013
Event23rd Workshop on Information Technology and Systems: Leveraging Big Data Analytics for Societal Benefits, WITS 2013 - Milan, Italy
Duration: Dec 14 2013Dec 15 2013

Other

Other23rd Workshop on Information Technology and Systems: Leveraging Big Data Analytics for Societal Benefits, WITS 2013
CountryItaly
CityMilan
Period12/14/1312/15/13

Keywords

  • Community analysis
  • Graph theory
  • Network analysis
  • News
  • Propagation
  • Twitter

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Bhattacharya, D., & Ram, S. (2013). Community analysis of news article sharing on Twitter. Paper presented at 23rd Workshop on Information Technology and Systems: Leveraging Big Data Analytics for Societal Benefits, WITS 2013, Milan, Italy.