Abstract
Loneliness has emerged as a chronic and persistent problem for a considerable fraction of the general population in the developed world. Concurrently, use of online social media by the same societies has steadily increased over the past two decades. The present study analyzed a recent large country-wide loneliness survey of 20,096 adults in the US using an unsupervised approach for systematic identification of clusters of respondents in terms of their social media use and representation among different socioeconomic subgroups. We studied the underlying population heterogeneity with a computational pipeline that was developed to gain insights into cluster- or group-specific patterns of loneliness. In particular, distributions of high loneliness were observed in groups of female users of Facebook and YouTube of certain age, race, marital, and socioeconomic status. For instance, among the group of predominantly YouTube users, we noted that non-Hispanic white female respondents of age 25–44 years who have high school or less education level and are single or never married have more significant high loneliness distribution. In fact, their high loneliness scores also seem to be associated with self-reported poorer physical and mental health outcomes.