Frontiers in Psychology (Jul 2023)

How does users' interest influence their click behavior?: evidence from Chinese online video media

  • Dongqi Li,
  • Dongqi Li,
  • Zihuang Tang,
  • Zihuang Tang,
  • Nan Zhao,
  • Nan Zhao

DOI
https://doi.org/10.3389/fpsyg.2023.1101396
Journal volume & issue
Vol. 14

Abstract

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Interest is one of the main factors motivating an individual's behavior, and its effect in the learning process has been widely confirmed in educational psychology. The purpose of this study was to explore the influence of individual interest, topic interest and situational interest on the user's video click behavior in the online video browsing situation. We constructed an online experiment in which each participant was asked to use questionnaires to assess their responses to video categories, titles, and covers from the video-sharing website, Bilibili. Based on these responses, we obtained individual interests, topic interests, situational interests, and click behavior of the participants toward the videos. Correlation, regression and mediation analyses were conducted to explore the effects and mechanisms of the three interests on click behavior. The results found: (1) individual interest may have a positive but relatively weaker effect on click behavior, and (2) topic interest and situational interest positively predicted click behavior in all categories. The mediation analysis found: (1) in the otomads and fashion categories, the effect of individual interest on click behavior was partially mediated by topic and situational interest, and (2) in the anime, digits, life, dance, music, game, entertainment, and knowledge categories, the effect of individual interest on click behavior was fully mediated by topic interest and situational interest. These results revealed the facilitating effects and different effect modes of individual, topic, and situational interest on click behavior. These findings shed light on the influence mechanism of interests on video click behavior in different video categories and provide new insights into related applications such as recommender.

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