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<p>With the rapid advancement of the Internet, emerging social media platforms facilitate real-time interaction among users, thereby rendering the impact of sentiments on behavior both faster and more complex. Analyzing and predicting the influence of sentiments on behavioral changes under various factors has become a critical issue. Grounded in the Emotions as Social Information (EASI) theory, this study conducts a comprehensive dynamic analysis of user sentimental changes from both personal and interpersonal perspectives. We employ HanLP for sentiment analysis and utilize structural equation modeling (SEM) and chi-square tests to analyze and validate the impact of sentiments on behavior. The results indicate that positive personal sentiment changes in users significantly enhance their purchase intentions. Furthermore, different users exhibit varying sentimental changes in their self-imitation behaviors. While positive emotions significantly influence users’ repetitive posting behavior, the effect of repeated video watching is less pronounced. This study, incorporating both real-time and video-time dimensions, dynamically validates that users who imitate others’ behaviors display more consistent positive emotions, providing evidence for sentimental contagion in user behaviors.</p>

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Dynamic analysis of barrage comments on sentimental influence and behavior

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月27日

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  • Qiao Wang,
  • Liang Liu,
  • Stephen John Turnbull,
  • Mitsuo Yoshida

摘要

With the rapid advancement of the Internet, emerging social media platforms facilitate real-time interaction among users, thereby rendering the impact of sentiments on behavior both faster and more complex. Analyzing and predicting the influence of sentiments on behavioral changes under various factors has become a critical issue. Grounded in the Emotions as Social Information (EASI) theory, this study conducts a comprehensive dynamic analysis of user sentimental changes from both personal and interpersonal perspectives. We employ HanLP for sentiment analysis and utilize structural equation modeling (SEM) and chi-square tests to analyze and validate the impact of sentiments on behavior. The results indicate that positive personal sentiment changes in users significantly enhance their purchase intentions. Furthermore, different users exhibit varying sentimental changes in their self-imitation behaviors. While positive emotions significantly influence users’ repetitive posting behavior, the effect of repeated video watching is less pronounced. This study, incorporating both real-time and video-time dimensions, dynamically validates that users who imitate others’ behaviors display more consistent positive emotions, providing evidence for sentimental contagion in user behaviors.