A Computational Approach to Automatic Prediction of Drunk-Texting

Alcohol abuse may lead to unsociable behavior such as crime, drunk driving, or privacy leaks. We introduce automatic drunk-texting prediction as the task of identifying whether a text was written when under the influence of alcohol. We experiment with tweets labeled using hashtags as distant supervision. Our classifiers use a set of N-gram and stylistic features to detect drunk tweets. Our observations present the first quantitative evidence that text contains signals that can be exploited to detect drunk-texting.

• Type: Journal
• Year: 2015
• Where: ACL
• Authors: Aditya Joshi, Abhijit Mishra, Balamurali A. R, Pushpak Bhattacharyya, Mark James Carman
• Keywords: ACL 2015, Computational Linguistics