Visualization, Technologies, or the Public? : Exploring the articulation of data-driven journalism in the Twittersphere

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

12 Scopus Citations
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Original languageEnglish
Pages (from-to)737-758
Journal / PublicationDigital Journalism
Issue number6
Publication statusPublished - 3 Jul 2018
Externally publishedYes


Data(-driven) journalism has triggered debates about whether this innovative storytelling and investigative approach, using data analytical and computational methods, better serves the public. Applying the concept of articulation, wherein an array of terms are juxtaposed and expressed together, this paper examines how the term “data-driven journalism” is represented on social media. Focusing on the Twittersphere as the research context, the paper employed the Twitter search application programming interface (API) to harvest all available public tweets (N = 6951) containing hashtags or keywords related to data-driven journalism within a four-week period in late 2016. A text-mining analysis of the contents of these tweets found that they focused extensively on journalistic practices, data visualization, and data analytical techniques. Further analysis on the hashtag co-occurrence network revealed that a number of hashtags bridged and organized the discussion of data-driven journalism in the Twittersphere. Some hashtags on technologies and commercial applications, such as “#dataviz,” “#bigdata,” and “#datajournalism,” were located at important positions in the network. In contrast, public-related terms, such as “#opendata” or “#opengovernment,” were mentioned in a limited way and positioned peripherally. Implications for journalism and society are discussed. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.

Research Area(s)

  • data-driven journalism, hashtag co-occurrence network, social network analysis, text mining, topic modeling, Twittersphere

Bibliographic Note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].