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arxiv: 1811.04655 · v2 · pith:LD6UIUL3new · submitted 2018-11-12 · 💻 cs.CL · cs.SI

Not Just Depressed: Bipolar Disorder Prediction on Reddit

classification 💻 cs.CL cs.SI
keywords bipolardisorderpredictiondifferencesredditusersaboveaccuracy
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Bipolar disorder, an illness characterized by manic and depressive episodes, affects more than 60 million people worldwide. We present a preliminary study on bipolar disorder prediction from user-generated text on Reddit, which relies on users' self-reported labels. Our benchmark classifiers for bipolar disorder prediction outperform the baselines and reach accuracy and F1-scores of above 86%. Feature analysis shows interesting differences in language use between users with bipolar disorders and the control group, including differences in the use of emotion-expressive words.

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  1. Leveraging Linguistic Characteristics for Bipolar Disorder Recognition with Gender Differences

    cs.IR 2019-07 unverdicted novelty 6.0

    Gender-enriched syntactic pattern features from Twitter data recognize bipolar disorder with F1 scores above 91%, outperforming TF-IDF, LIWC, ELMO, and BERT baselines.