Analysing expression of loneliness and insomnia through social intelligence analysis.

Background: Loneliness and insomnia are mutually occurring conditions. This paper investigates whether keywords depicting loneliness and insomnia are expressed together on social media. Understanding loneliness through data fills the gaps or validates the literature on loneliness from sociological and psychological perspectives. Loneliness is associated with various physical and mental health conditions but there are opportunities to understand it from the perspectives and lens of health informatics through social media data. Because loneliness is a subjective phenomenon, therefore, the self-reporting nature of social media data can provide an intimate glimpse into the feelings associated with loneliness.

Methods: This study uses sentiment analysis of collected tweets on loneliness and insomnia to filter out the tweets that have negative connotations. Those tweets are then further analysed to find out categories and themes associated with loneliness and insomnia.

Results: Through the frequency of word occurrence analysis, it was seen that the association between loneliness and insomnia can be found. The association, in the tweets analysed, is mediated by words denoting depressive symptoms. Moreover, the themes and categories which are associated with the expression of both loneliness and insomnia are those of personal feelings and time.