Visualization, technologies, or the public? A text mining analysis of the articulation of data-driven journalism in the Twittersphere

Research output: Contribution to conferencePaperpeer-review

Abstract

Data-driven journalism has triggered debates that whether these innovative approaches, such as using data analytical and computational methods, better serve the public. Applying the concept of articulation, wherein an array of terms are juxtaposed and expressed together, this paper examined how the term “data-driven journalism” is discursively constructed by ordinary people on social media. Using the Twitter application programming interface (API), this paper harvested all available public tweets (n = 2,597) containing hashtags or keywords related to data-driven journalism within two weeks in late October 2016. Text-mining indicated these tweets focused intensively on data visualization and data analytical techniques. Further analysis on the hashtag co-occurrence network, i.e., a network established via creating edges between two or more hashtags appearing together within the same tweet, revealed that journalism and visualization-related hashtags were located at important positions in the network; in contrast, public-related terms, such as “#opendata” or “#opengovernment,” were positioned peripherally.
Original languageEnglish
Publication statusPublished - May 2017
EventICA 2017 - 67th Annual International Communication Association Conference: Interventions. Communication Research and Practice - San Diego, CA, United States
Duration: 25 May 201729 May 2017
https://convention2.allacademic.com/one/ica/ica17/

Conference

ConferenceICA 2017 - 67th Annual International Communication Association Conference
Country/TerritoryUnited States
CitySan Diego, CA
Period25/05/1729/05/17
Internet address

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