Employing a Chatbot for News Dissemination during Crisis: Design, Implementation and Evaluation

The use of chatbots in news media platforms, although relatively recent, offers many advantages to journalists and media professionals and, at the same time, facilitates users’ interaction with useful and timely information. This study shows the usability of a news chatbot during a crisis situation, employing the 2020 COVID-19 pandemic as a case study. The basic targets of the research are to design and implement a chatbot in a news media platform with a two-fold aim in regard to evaluation: first, the technical effort of creating a functional and robust news chatbot in a crisis situation both from the AI perspective and interoperability with other platforms, which constitutes the novelty of the approach; and second, users’ perception regarding the appropriation of this news chatbot as an alternative means of accessing existing information during a crisis situation. The chatbot designed was evaluated in terms of effectively fulfilling the social responsibility function of crisis reporting, to deliver timely and accurate information on the COVID-19 pandemic to a wide audience. In this light, this study shows the advantages of implementing chatbots in news platforms during a crisis situation, when the audience’s needs for timely and accurate information rapidly increase.

[1]  Andrea L. Guzman,et al.  Automation, Journalism, and Human–Machine Communication: Rethinking Roles and Relationships of Humans and Machines in News , 2019, Digital Journalism.

[2]  Patric R. Spence,et al.  Searching for questions, original thoughts, or advancing theory: Human-machine communication , 2019, Comput. Hum. Behav..

[3]  Heather Ford,et al.  Newsbots That Mediate Journalist and Audience Relationships , 2019, Algorithms, Automation, and News.

[4]  Robert Dale,et al.  The return of the chatbots , 2016, Natural Language Engineering.

[5]  Asbjørn Følstad,et al.  Chatbots and the new world of HCI , 2017, Interactions.

[6]  Nicholas Diakopoulos,et al.  News Bots , 2016 .

[7]  Yu Zhang,et al.  Memory Pattern Identification for Feedback Tracking Control in Human-Machine Systems. , 2019, Human factors.

[8]  Ben Shneiderman,et al.  Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy , 2020, Int. J. Hum. Comput. Interact..

[9]  Franz Krüger.  Ethical journalism in a time of AIDS , 2005, African journal of AIDS research : AJAR.

[10]  Yannis Charalabidis,et al.  Transforming the communication between citizens and government through AI-guided chatbots , 2019, Gov. Inf. Q..

[11]  Heather H. Mitchell,et al.  Social Cues in Animated Conversational Agents , 2005 .

[12]  Konstantin Dörr,et al.  Ethical Challenges of Algorithmic Journalism , 2017 .

[13]  Lucia D'Acunto,et al.  Exposure diversity as a design principle for recommender systems , 2018 .

[14]  Rhianne Jones,et al.  Public Service Chatbots: Automating Conversation with BBC News , 2019, Algorithms, Automation, and News.

[15]  Andreas Veglis,et al.  Chatbots on the Rise: A New Narrative in Journalism , 2019, Studies in Media and Communication.

[16]  Damian Trilling,et al.  Should We Worry About Filter Bubbles? , 2016 .

[17]  Andreas Veglis,et al.  The Mediated Data Model of Communication Flow: Big Data and Data Journalism , 2018 .

[18]  Christopher B. Mann,et al.  Can Conversing with a Computer Increase Turnout? Mobilization Using Chatbot Communication , 2020, Journal of Experimental Political Science.

[19]  Damian Trilling,et al.  My Friends, Editors, Algorithms, and I , 2018, Digital Journalism.