  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.
