LonelyText: A Short Messaging Based Classification of Loneliness
This addresses loneliness prediction for mental health applications, but it appears incremental as it builds on existing text classification methods without specifying major breakthroughs.
The authors tackled the problem of predicting loneliness by analyzing language patterns in instant messaging, showing promising directions for text mining in this area.
Loneliness does not only have emotional implications on a person but also on his/her well-being. The study of loneliness has been challenging and largely inconclusive in findings because of the several factors that might correlate to the phenomenon. We present one approach to predicting this event by discovering patterns of language associated with loneliness. Our results show insights and promising directions for mining text from instant messaging to predict loneliness.