News from Messenger? A Cross-National Comparative Study of News Media's Audience Engagement Strategies via Facebook Messenger Chatbots

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

2 Scopus Citations
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Original languageEnglish
Journal / PublicationDigital Journalism
Publication statusOnline published - 24 Nov 2022
Externally publishedYes


As an emerging audience engagement channel for news organizations, news chatbots can interact with and attract audiences in a conversational manner. The present study applies the comparative digital journalism frameworks and examines how society-level factors—such as media systems and information communication technology’s development—explain chatbot implementation on social media platforms. We surveyed 365 news organizations across 38 countries or regions and inspected their Facebook Messenger accounts with a mixed-methods approach. We found that less than half of the surveyed news organizations implemented Messenger, and only 67 Messengers were responsive—i.e. able to produce at least one response. We used the walkthrough method to interact with the Messengers with 22 pre-defined search queries on information seeking and navigation related to COVID-19. Then we used qualitative content analysis to examine the contents generated by the Messengers. Some Messengers are out of service or could only provide limited services (e.g. generating templated responses or closed-ended options). The Messengers in different news organizations demonstrated great variations in their capacity to understand the queries and interact with the audiences and reparative strategies to handle search failure. We proposed a three-category typology of news chatbots and offered practical and constructive suggestions for news organizations. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Research Area(s)

  • audience engagement, automated journalism, comparing digital journalism, computational journalism, conversational journalism, news chatbots