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- W2950507975 abstract "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." @default.
- W2950507975 created "2019-06-27" @default.
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- W2950507975 date "2016-10-04" @default.
- W2950507975 modified "2023-09-25" @default.
- W2950507975 title "A Computational Approach to Automatic Prediction of Drunk Texting" @default.
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