The outbreak of the COVID-19 pandemic triggers infodemic over online social media, which significantly impacts public health around the world, both physically and psychologically. In this paper, we study the impact of the pandemic on the mental health of influential social media users, whose sharing behaviours significantly promote the diffusion of COVID-19 related information. Specifically, we focus on subjective well-being (SWB), and analyse whether SWB changes have a relationship with their bridging performance in information diffusion, which measures the speed and wideness gain of information transmission due to their sharing. We accurately capture users' bridging performance by proposing a new measurement. Benefiting from deep-learning natural language processing models, we quantify social media users' SWB from their textual posts. With the data collected from Twitter for almost two years, we reveal the greater mental suffering of influential users during the COVID-19 pandemic. Through comprehensive hierarchical multiple regression analysis, we are the first to discover the strong {relationship} between social users' SWB and their bridging performance.
翻译:COVID-19大流行的爆发引发了网上社交媒体的流行,对全世界公众的生理和心理都产生了重大影响。在本文中,我们研究了这一大流行对有影响力的社会媒体用户心理健康的影响,这些用户的共享行为极大地促进了COVID-19相关信息的传播。具体地说,我们注重主观福祉(SWB),并分析SWB的变化是否与其信息传播的过渡性表现有关系,后者衡量信息传播因共享而获得的速度和广度。我们通过提出新的衡量标准来准确地捕捉用户的连接性表现。我们从深入学习的自然语言处理模型中受益,从他们的文本文章中量化社交媒体用户的SWB。我们从推特上收集的数据近两年来揭示了有影响力的用户在COVID-19大流行期间遭受更大的精神痛苦。我们通过全面的等级多重回归分析,第一个发现社会用户SWB及其连接性表现之间的强大关系。