随着互联网日益深入生活，人们已经习惯通过它获取时事新闻，进行娱乐和社交交流。尤其是社交媒体平台（如抖音、快手、小红书等）的广泛使用，让人们在接受外界信息的同时，长时间暴露在他人的情绪之中，这可能会导致数字情绪传染。数字情绪传染程度可能会受社交媒体使用者类型的影响。本论文从社交媒体使用者的主动和被动分类出发，通过了解主动和被动两类用户的情感特点，揭示人们使用社交媒体时的心理动态以及对用户幸福感的影响。 本研究通过问卷调查、行为实验、眼动测量等方法，对主动和被动社交媒体用户的心理特征进行了分析，重点关注情绪相关的心理特质与状态。研究 1 通过问卷调查（N = 190）考察主动和被动用户在抑郁症状、焦虑水平、述情障碍等主要情绪相关的心理特质方面的可能差异。结果表明，主动和被动用户的抑郁症状存在显著差异，被动用户相较于主动用户的抑郁程度更高；两类用户在焦虑水平或述情障碍方面并未表现出明显差异。研究 2 通过行为实验（N = 366）考察用户观看不同情绪视频时的情绪反应。结果表明，被动用户在观看正性情绪视频时表现出较低强度的积极情绪，在观看大多数负性情绪视频时表现出较低强度的消极情绪；主动用户则在观看正性和负性情绪视频时都表现出了更强烈的积极和消极情感。研究 3 通过眼动测量（N = 12）考察用户观察带弹幕的典型社交媒体视频时的眼动模式。结果表明，相较于主动用户，被动用户更多关注弹幕评论，表现出对弹幕内容的更多的注视次数。 综上，本论文研究发现，主动和被动社交媒体用户在情绪相关的心理特质与状态方面存在显著差异：主动社交媒体用户抑郁水平较低、数字情绪传染程度更高，观看社交媒体视频时眼动模式不同。以上结果为理解社交媒体对用户情绪心理特点提供了实证数据支撑，对开展基于社交媒体的用户情绪心理健康调节具有潜在的应用价值。

Due to the widespread use of social media, individuals spend significant time on these platforms, frequently exposing themselves to the emotional expressions of others. This exposure can lead to their emotional expressions becoming more similar to those of others, a process called digital emotional contagion. For instance, one might smile and feel happy when watching a video of a baby giggling or a video of playful puppies. However, the level of happiness may vary depending on whether one is an active or passive social media user. Therefore, understanding these two user groups’ emotions can shed light on the psychological dynamics of social media and its impact on users’ well-being.The study examines the psychological profiles of active and passive social media users using a combination of survey, behavioral experiment, and eye-tracking methods, with a focus on emotion-related traits and emotional responses. Experiment 1 employed a survey-based approach (N = 190) and revealed a higher level of depressive symptoms for passive users but no significant differences in anxiety levels or alexithymia between the two user types. Experiment 2 (N = 366) showed that active users in general reported a higher level of emotional experience when watching emotional videos as compared to passive users. Experiment 3 (N = 12) further utilized the eye-tracking technique, and the results illustrated that passive users paid more attention to the bullet comments when watching the typical social media videos with bullet comments, as reflected by their significantly higher fixation counts compared to active users. To sum up, our study illustrates the psychological profile of active users as a lower depression level and a higher emotional contagion level, possibly due to their increased attention to the content per itself rather than the social information. Our findings provide evidence for the emotion-related psychological characteristics of social media users and could be potentially useful for social-media-based mental health adjustment.