AUTHOR=Li Dongqi , Tang Zihuang , Zhao Nan 

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

JOURNAL=Frontiers in Psychology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1101396

DOI=10.3389/fpsyg.2023.1101396

ISSN=1664-1078

ABSTRACT=Interest is one of the main factors motivating individual’s behavior, and its effect in learning process has been widely confirmed in the 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. In this study, we measured 264 users' individual interest, topic interest, situational interest, and click probability for videos in ten video categories of the Bilibili video site. Correlation, regression and mediation analyses were conducted to explore the effects and mechanisms of the three interests on click behavior. The correlation and regression analysis found: (1) Individual interest may have positive but relatively weaker effect on click behavior. (2) Topic interest and situational interest positively predicted click behavior in all categories. The mediation analysis found: (1) there was no direct or indirect effect between individual interest and click behavior in the dance and game categories. (2) In the anime, life and entertainment categories, the effect of individual interest on click behavior was partially mediated by topic and situational interest. (3) In the otomads, fashion, knowledge, digits, and music 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 interest, topic interest 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 for related applications such as recommender.