Journalists’ Adoption and Media’s Coverage of Data-driven Journalism: a Case of Hong Kong

Xinzhi ZHANG*, Minyi Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Data-driven journalism is gaining a presence in news organizations. Most existing studies on journalists’ adoption of and media’s discourse around data-driven journalism have focused on Western contexts. The present study focuses on Hong Kong, a non-Western society where data-driven journalism is nascent. This study applies the diffusion of innovation theory, the technology acceptance model, and the trading zone framework to explain how journalists adopt data-driven journalism and how this journalistic practice is communicated to the public through media coverage. An online survey was conducted with news professionals in local media organizations (n = 255), as was a supplementary content analysis of news articles on data-driven journalism published in Hong Kong media in 2009–2019 (n = 57). Survey results revealed that perceived ease of use and perceived popularity were positively associated with the adoption of data-driven journalism. The more designers were involved in the news production process, the more likely it was for participants to adopt data-driven journalism. Additionally, most media coverage highlighted the positive outcomes of data-driven journalism—particularly its observability and usefulness—as well as the importance of interdisciplinary collaboration. The implications of applying data science to news production and the sociotechnical context of Hong Kong are discussed.

Original languageEnglish
JournalJournalism Practice
DOIs
Publication statusAccepted/In press - 2020

Scopus Subject Areas

  • Communication

User-Defined Keywords

  • data and media communication
  • Data journalism
  • Data-driven journalism
  • diffusion of innovation
  • digital journalism
  • Hong Kong
  • interdisciplinary collaboration
  • journalism education
  • technology acceptance model
  • trading zone framework

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