Suicidal Ideation and Mental Disorder Detectionwith Attentive Relation Networks
Table 5: Selected linguistic statistical information of UMD dataset extracted by LIWC
['Linguistic clues', 'Label -1', 'Label 0', 'Label 1']
We have a brief exploratory analysis on the data. Some selected linguistic statistical information of UMD dataset extracted by Linguistic Inquiry and Word Count software (LIWC) The risk of suicide increases among labels of -1, 0, and 1. The linguistic inquiry results show that negative emotion, anxiety, and sadness are expressed more in posts with high-level suicide risk. The same trend exists in family issues, death-related mentions and swear words. Naturally, positive emotions are less presented in posts with high suicide risk.