A Macroscopic Analysis of News Content in Twitter

Momin M. Malik, Jürgen Pfeffer

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Previous literature has considered the relevance of Twitter to journalism, for example as a tool for reporters to collect information and for organizations to disseminate news to the public. We consider the reciprocal perspective, carrying out a survey of news media-related content within Twitter. Using a random sample of 1.8 billion tweets over four months in 2014, we look at the distribution of activity across news media and the relative dominance of certain news organizations in terms of relative share of content, the Twitter behavior of news media, the hashtags used in news content versus Twitter as a whole, and the proportion of Twitter activity that is news media-related. We find a small but consistent proportion of Twitter is news media-related (0.8 percent by volume); that news media-related tweets focus on a different set of hashtags than Twitter as a whole, with some hashtags such as those of countries of conflict (Arab Spring countries, Ukraine) reaching over 15 percent of tweets being news media-related; and we find that news organizations’ accounts, across all major organizations, largely use Twitter as a professionalized, one-way communication medium to promote their own reporting. Using Latent Dirichlet Allocation topic modeling, we also examine how the proportion of news content varies across topics within 100,000 #Egypt tweets, finding that the relative proportion of news media-related tweets varies vastly across different subtopics. Over-time analysis reveals that news media were among the earliest adopters of certain #Egypt subtopics, providing a necessary (although not sufficient) condition for influence.

Original languageEnglish
Pages (from-to)955-979
Number of pages25
JournalDigital Journalism
Volume4
Issue number8
DOIs
StatePublished - 16 Nov 2016
Externally publishedYes

Keywords

  • Twitter
  • computational
  • news media
  • social media
  • topic modeling

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