Publication | Open Access
Understanding User Perception of Automated News Generation System
29
Citations
39
References
2020
Year
Unknown Venue
Natural Language ProcessingEngineeringComputational JournalismUser-generated ContentUser ExperienceNews SystemIndividualized NewsHuman-computer InteractionInterface DesignNews AnalyticsCommunicationNews SemanticsArtsContent AnalysisUser PerceptionJournalismText MiningInteractive Journalism
Automated journalism refers to the generation of news articles using computer programs. Although it is widely used in practice, its user experience and interface design remain largely unexplored. To understand the user perception of an automated news system, we designed NewsRobot, a research prototype that automatically generated news on major events of the PyeongChang 2018 Winter Olympic Games in real-time. It produces six types of news by combining two kinds of content (general/individualized) and three styles (text, text+image, text+image+sound). A total of 30 users participated in using NewsRobot, completing surveys and interviews on their experience. Our findings are as follows: (1) Users preferred individualized news yet considered it less credible, (2) more presentation elements were appreciated but only if their quality was assured, and (3) NewsRobot was considered factual and accurate yet shallow in depth. Based on our findings, we discuss implications for designing automated journalism user interfaces.
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