Abstract

The use of algorithms is beginning to replace human activities in the news business, and the presence of this technique will only continue to grow. The ways in which public news readers perceive the quality of news articles written by algorithms and how this perception differs based on cultural conditioning remain issues of debate. Informed by the heuristic-systematic model (HSM) and the similarity-attraction theory, we attempted to answer these questions by conducting a three-way one-way analysis of variance (ANOVA) test with a 2 (author: algorithm vs. human journalist) × 2 (media: traditional media vs. online media) × 2 (cultural background: the US vs. South Korea) between-subjects experiment (N = 360). Our findings revealed that participants perceived the quality of news articles written by algorithms to be higher than those written by human journalists. We also found that when news consumption occurs online, algorithm-generated news tends to be rated higher than human-written news in terms of quality perception. Further, we identified a three-way interaction effect of media types, authors, and cultural backgrounds on the quality perception of news articles. As, to the best of our knowledge, this study is the first to theoretically examine how news readers perceive algorithm-generated news from a cultural point of view, our research findings may hold important theoretical and practical implications.

Highlights

  • The rapid development of digital technology is driving changes in various fields of society, and the field of media is no exception to this evolution

  • Apart from the main survey, participants completed a manipulation check designed to assess whether they identified the author of news stories as a human journalist, an algorithm, or whether they were unsure about the type of author

  • According to the result of carrying out a planned contrast to examine the detailed interactions between variables, when news users read the news in traditional media, they perceived the quality of news articles written by human journalists (M = 3.96, SD = 0.57) to be higher than those generated by algorithms (M = 3.53, SD = 0.87; F (1, 178) = 14.992, p < 0.05)

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Summary

Introduction

The rapid development of digital technology is driving changes in various fields of society, and the field of media is no exception to this evolution. News organizations are making efforts to improve the efficiency of news generation by employing news-generating algorithms to simulate natural language. AI has started to significantly impact general media and news agencies under the name of “robot journalism” ( known as computational journalism, algorithm journalism, or machine-written journalism) [2,3]. Robot journalism has been introduced to, or recognized by, the general public since 2010 and refers to the automatic generation of news articles using AI-based algorithms with no involvement of human journalists [2].

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