  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.
