Topic model for identifying suicidal ideation in Chinese microblog

29th Pacific Asia Conference on Language, Information and Computation, PACLIC 2015

Volumn , Issue , 2015, Pages 553-562

  Huang, Xiaolei ^a   Li, Xin ^a   Zhang, Lei ^b   Liu, Tianli ^c   Chiu, David ^d   Zhu, Tingshao ^a,e  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b UNIVERSITY OF JINAN   (China)

^c PEKING UNIVERSITY   (China)

^d UNIVERSITY OF PUGET SOUND   (United States)

^e INSTITUTE OF PSYCHOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL LINGUISTICS; LEARNING ALGORITHMS; LEARNING SYSTEMS;

EMBEDDING TECHNIQUE; ON-LINE SOCIAL NETWORKS; ONLINE BEHAVIOR; PROTOTYPE SYSTEM; REAL-TIME ASSESSMENT; SUICIDAL IDEATION; TOPIC MODELING; USER-GENERATED;

SOCIAL NETWORKING (ONLINE);

EID: 84967163556     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (34)

1. David M Blei, Andrew Y Ng, and Michael I Jordan. 2003. Latent dirichlet allocation. the Journal of machine Learning research, 3:993-1022.
2. Peter F Brown, Peter V Desouza, Robert L Mercer, Vincent J Della Pietra, and Jenifer C Lai. 1992. Classbased n-gram models of natural language. Computational linguistics, 18(4):467-479.
3. Chih-Chung Chang and Chih-Jen Lin. 2011. Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST), 2(3):27.
4. Munmun De Choudhury, Michael Gamon, Scott Counts, and Eric Horvitz. 2013. Predicting depression via social media. In ICWSM.
5. Zhendong Dong and Qiang Dong. 2003. Hownet-A hybrid language and knowledge resource. In Natural Language Processing and Knowledge Engineering, 2003. Proceedings. 2003 International Conference on, pages 820-824. IEEE.
6. King-wa Fu, Qijin Cheng, Paul WC Wong, and Paul SF Yip. 2013. Responses to a self-presented suicide attempt in social media: A social network analysis. Crisis: The Journal of Crisis Intervention and Suicide Prevention, 34(6):406.
7. Rui Gao, Bibo Hao, He Li, Yusong Gao, and Tingshao Zhu. 2013. Developing simplified chinese psychological linguistic analysis dictionary for microblog. In Brain and Health Informatics, pages 359-368. Springer.
8. Li Guan, Bibo Hao, and Tingshao Zhu. 2014. How did the suicide act and speak differently online? behavioral and linguistic features of china's suicide microblog users. arXiv preprint arXiv:1407.0466.
9. Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian HWitten. 2009. The weka data mining software: an update. ACM SIGKDD explorations newsletter, 11(1):10-18.
10. Jared Jashinsky, Scott H Burton, Carl L Hanson, Josh West, Christophe Giraud-Carrier, Michael D Barnes, and Trenton Argyle. 2013. Tracking suicide risk factors through twitter in the us.
11. Stanley R Kay, Abraham Flszbein, and Lewis A Opfer. 1987. The positive and negative syndrome scale (panss) for schizophrenia. Schizophrenia bulletin, 13(2):261.
12. Lin Li, Ang Li, Bibo Hao, Zengda Guan, and Tingshao Zhu. 2014a. Predicting active users' personality based on micro-blogging behaviors. PLoS ONE, 9(e84997).
13. Tim MH Li, Michael Chau, Paul SF Yip, and Paul WC Wong. 2014b. Temporal and computerized psycholinguistic analysis of the blog of a chinese adolescent suicide.
14. Chenghua Lin and Yulan He. 2009. Joint sentiment/topic model for sentiment analysis. In Proceedings of the 18th ACM conference on Information and knowledge management, pages 375-384. ACM.
15. Huijie Lin, Jia Jia, Quan Guo, Yuanyuan Xue, Jie Huang, Lianhong Cai, and Ling Feng. 2014. Psychological stress detection from cross-media microblog data using deep sparse neural network.
16. David D Luxton, Jennifer D June, and Julie T Kinn. 2011. Technology-based suicide prevention: current applications and future directions. Telemedicine and e-Health, 17(1):50-54.
17. Leonard L Martin, David W Ward, John W Achee, and Robert S Wyer. 1993. Mood as input: People have to interpret the motivational implications of their moods. Journal of Personality and Social Psychology, 64(3):317.
18. Andrew Kachites McCallum. 2002. Mallet: A machine learning for language toolkit.
19. Qiaozhu Mei, Xu Ling, Matthew Wondra, Hang Su, and ChengXiang Zhai. 2007. Topic sentiment mixture: modeling facets and opinions in weblogs. In Proceedings of the 16th international conference onWorld Wide Web, pages 171-180. ACM.
20. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, pages 3111-3119.
21. World Health Organization et al. 2014. Preventing suicide: A global imperative. World Health Organization.
22. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2):1-135.
23. John Pestian, Henry Nasrallah, Pawel Matykiewicz, Aurora Bennett, and Antoon Leenaars. 2010. Suicide note classification using natural language processing: A content analysis. Biomedical informatics insights, 2010(3):19.
24. John P Pestian, Pawel Matykiewicz, Michelle Linn-Gust, Brett South, Ozlem Uzuner, Jan Wiebe, K Bretonnel Cohen, John Hurdle, and Christopher Brew. 2012. Sentiment analysis of suicide notes: A shared task. Biomedical informatics insights, 5(Suppl 1):3.
25. Philip Resnik, Anderson Garron, and Rebecca Resnik. 2013. Using topic modeling to improve prediction of neuroticism and depression. In Proceedings of the 2013 Conference on Empirical Methods in Natural, pages 1348-1353. Association for Computational Linguistics.
26. M David Rudd, Alan L Berman, Thomas E Joiner, Matthew K Nock, Morton M Silverman, Michael Mandrusiak, Kimberly Van Orden, and Tracy Witte. 2006. Warning signs for suicide: Theory, research, and clinical applications. Suicide and Life-Threatening Behavior, 36(3):255-262.
27. Jian Sun. 2014. Ansj Chinese Lexical Analysis System. Website. http://ansj.org/.
28. Kristina Toutanova, Dan Klein, Christopher D. Manning, and Yoram Singer. 2003. Feature-Rich Partof-Speech Tagging with a Cyclic Dependency Network. In North American Chapter of the Association for Computational Linguistics.
29. Peter D. Turney and Patrick Pantel. 2010. From Frequency to Meaning: Vector Space Models of Semantics. Computing Research Repository, abs/1003.1.
30. Hongning Wang, Yue Lu, and Chengxiang Zhai. 2010. Latent aspect rating analysis on review text data: a rating regression approach. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 783-792. ACM.
31. Xinyu Wang, Chunhong Zhang, Yang Ji, Li Sun, Leijia Wu, and Zhana Bao. 2013. A depression detection model based on sentiment analysis in microblog social network. In Trends and Applications in Knowledge Discovery and Data Mining, pages 201-213. Springer.
32. Casey Whitelaw, Navendu Garg, and Shlomo Argamon. 2005. Using appraisal groups for sentiment analysis. In Proceedings of the 14th ACM international conference on Information and knowledge management, pages 625-631. ACM.
33. Chung-Hsien Wu, Liang-Chih Yu, and Fong-Lin Jang. 2005. Using semantic dependencies to mine depressive symptoms from consultation records. Intelligent Systems, IEEE, 20(6):50-58.
34. Liang-Chih Yu and Chun-Yuan Ho. 2014. Identifying emotion labels from psychiatric social texts using independent component analysis. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, pages 837-847, Dublin, Ireland, August. Dublin City University and Association for Computational Linguistics.