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Depression Tendency Recognition Model Based on College Student’s Microblog Text

Abstract : In order to solve the issue of identifying depression tendency hidden in microblog text, a depression emotional inclination recognition model based on emotional decay factor is proposed. Make the self-rating depression scale, collect students’ microblog text and ask the psychology specialist to annotate the microblog artificially. Construct the depressive emotion dictionary, and then build a depression emotion classifier based on support vector machine. Considering the continuity of depression mood swing, the mathematical model of emotional decay factor is constructed to realize the continuity of discrete emotional state. The experimental results show that the model can effectively identify the depression of user for a period of time, the recognition accuracy rate is 83.82%.
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Submitted on : Friday, June 22, 2018 - 10:43:00 AM
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Jie Qiu, Junbo Gao. Depression Tendency Recognition Model Based on College Student’s Microblog Text. 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.351-359, ⟨10.1007/978-3-319-68121-4_38⟩. ⟨hal-01820904⟩



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