• Title/Summary/Keyword: 뉴스 추천 메커니즘

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The Effect of Representativeness in News Recommendation Mechanisms on Audience Reactions in Online News Portals (대표성 기반 뉴스 추천 메커니즘이 온라인 뉴스 포탈의 독자 반응에 미치는 영향)

  • Lee, Un-Kon
    • The Journal of Society for e-Business Studies
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    • v.21 no.2
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    • pp.1-22
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    • 2016
  • News contents has been collected, selected, edited and sometimes distorted by the news recommendation mechanisms of online portals in nowadays. Prior studies had not confirmed the consensus of newsworthiness, and they had not tried to empirically validate the impacts of newsworthiness on audience reactions. This study challenged to summarize the concepts of newsworthiness and validate the impact of representativeness of both editor's and audience's perspective on audience reactions as perceived news quality, trust on news portal, perceived usefulness, service satisfaction, loyalty, continuous usage intention, and word-of-mouth intention by adopting the representativeness heuristics method and information adoption model. 357 valid data had been collected using a scenario survey method. Subjects in each groups are exposed by 3 news recommendation mechanisms: 1) the time-priority news exposure mechanism (control group), 2) the reference-score-based news recommendation mechanism (a single treatment group), and 3) the major-news-priority exposure mechanism sorting by the reference scores made by peer audiences (the mixed treatment group). Data had been analyzed by the MANOVA and PLS method. MANOVA results indicate that only mixed method of both editor and audience recommendation mechanisms impacts on perceived news quality and trust. PLS results indicate that perceived news quality and trust could significantly affect on the perceived usefulness, service satisfaction, loyalty, continuance usage, and word-of-mouth intention. This study would contributions to empathize the role of information technology in media industry, to conceptualize the news value in the balanced views of both editors and audiences, and to empirically validate the benefits of news recommendation mechanisms in academy. For practice, the results of this study suggest that online news portals would be better to make mixed news recommendation mechanisms to attract audiences.