A Computational Analysis of the Language of Drug Addiction
Carlo Strapparava, Rada F. Mihalcea · 2017
We present a computational analysis of the language of drug users when talking about their drug experiences.We introduce a new dataset of over 4,000 descriptions of experiences reported by users of four main drug types, and show that we can predict with an F1-score of up to 88% the drug behind a certain experience.We also perform an analysis of the dominant psycholinguistic processes and dominant emotions associated with each drug type, which sheds light on the characteristics of drug users.