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Teenagers’ Stress Detection Based on Time-Sensitive Micro-blog Comment/Response Actions

Abstract : Accurately detecting psychological stress in time is a significant issue in the modern stressful society, especially for adolescents who are not mature enough to cope with pressure well. Micro-blog offers a new channel for teens’ stress detection, since more and more teenagers nowadays prefer to express themselves on the lively virtual social networks. Previous work mainly rely on tweeting contents to detect tweeters’ psychological stress. However, a tweet is limited to 140 characters, which are too short to provide enough information to accurately figure out its tweeter’s stress. To overcome the limitation, this paper proposes to leverage details of social interactions between tweeters and their following friends (i.e., time-sensitive comment/response actions under a tweet) to aid stress detection. Experimental results through a real user study show that time sensitivity of comment/response acts plays a significant role in stress detection, and involving such interaction acts can improve the detection performance by 23.5% in F-measure over that without such interactions.
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Liang Zhao, Jia Jia, Ling Feng. Teenagers’ Stress Detection Based on Time-Sensitive Micro-blog Comment/Response Actions. 4th IFIP International Conference on Artificial Intelligence in Theory and Practice (AI 2015), Oct 2015, Daejeon, South Korea. pp.26-36, ⟨10.1007/978-3-319-25261-2_3⟩. ⟨hal-01383941⟩

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