Classification of helpful comments on online suicide watch forums

ACM-BCB 2016 - 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

Volumn , Issue , 2016, Pages 32-40

  Kavuluru, Ramakanth ^a   Williams, Amanda G ^b   Ramos Morales, María ^c   Haye, Laura ^a   Holaday, Tara ^a   Cerel, Julie ^a  

^a UNIVERSITY OF KENTUCKY   (United States)

^b WESTERN KENTUCKY UNIVERSITY   (United States)

^c UNIVERSITY OF KENTUCKY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; BIOINFORMATICS; INFORMATION SCIENCE; LEARNING SYSTEMS; MODERATORS; WATCHES;

AUTOMATIC IDENTIFICATION; CONTENT-BASED FEATURES; IMMEDIATE FEEDBACKS; MACHINE LEARNING APPROACHES; MENTAL HEALTH; MESSAGE BOARDS; RESEARCH COMMUNITIES; SOCIAL MEDIA WEBSITES;

HEALTH;

EID: 85009774221     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2975167.2975170     Document Type: Conference Paper

References (36)

1. A. L. Berman, M. M. Silverman, and B. M. Bongar. Comprehensive textbook of suicidology. Guilford Press, 2000.
2. P. Burnap, W. Colombo, and J. Scourfield. Machine classification and analysis of suicide-related communication on twitter. In Proceedings of the 26th ACM Conference on Hypertext & Social Media, pages 75-84. ACM, 2015.
3. D. Cameron, G. A. Smith, R. Daniulaityte, A. P. Sheth, D. Dave, L. Chen, G. Anand, R. Carlson, K. Z. Watkins, and R. Falck. Predose: A semantic web platform for drug abuse epidemiology using social media. Journal of biomedical informatics, 46(6):985-997, 2013.
4. L. E. Charles-Smith, T. L. Reynolds, M. A. Cameron, M. Conway, E. H. Lau, J. M. Olsen, J. A. Pavlin, M. Shigematsu, L. C. Streichert, K. J. Suda, et al. Using social media for actionable disease surveillance and outbreak management: A systematic literature review. PloS one, 10(10):e0139701, 2015.
5. G. B. Colombo, P. Burnap, A. Hodorog, and J. Scourfield. Analysing the connectivity and communication of suicidal users on twitter. Computer Communications, 73:291-300, 2016.
6. M. De Choudhury and S. De. Mental health discourse on Reddit: Self-disclosure, social support, and anonymity. In Proceedings of the Eighth AAAI International Conference on Weblogs and Social Media (ICWSM), pages 71-80. Citeseer, 2014.
7. M. De Choudhury, M. Gamon, S. Counts, and E. Horvitz. Predicting depression via social media. In Proceedings of the Seventh AAAI International Conference on Weblogs and Social Media (ICWSM), pages 128-137, 2013.
8. M. De Choudhury, E. Kiciman, M. Dredze, G. Coppersmith, and M. Kumar. Discovering shifts to suicidal ideation from mental health content in social media. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pages 2098-2110. ACM, 2016.
9. M. de Marneffe, B. MacCartney, and C. Manning. Generating Typed Dependency Parses from Phrase Structure Parses. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC), pages 449-454, 2006.
10. J. L. Fleiss. Measuring nominal scale agreement among many raters. Psychological bulletin, 76(5):378, 1971.
11. A. Fritzsche, B. Schlier, G. Oettingen, and T. M. Lincoln. Mental contrasting with implementation intentions increases goal-attainment in individuals with mild to moderate depression. Cognitive Therapy and Research, pages 1-8, 2016.
12. S. Han and R. Kavuluru. On assessing the sentiment of general tweets. In Canadian Conference on Artificial Intelligence, pages 181-195. Springer, 2015.
13. P. A. Harris, R. Taylor, R. Thielke, J. Payne, N. Gonzalez, and J. G. Conde. Research electronic data capture (REDCap) - a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of biomedical informatics, 42(2):377-381, 2009.
14. P. Jansen, M. Surdeanu, and P. Clark. Discourse complements lexical semantics for non-factoid answer reranking. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014, Volume 1: Long Papers, pages 977-986, 2014.
15. J. Jashinsky, S. H. Burton, C. L. Hanson, J. West, C. Giraud-Carrier, M. D. Barnes, and T. Argyle. Tracking suicide risk factors through twitter in the us. Crisis, 35(1):51-59, 2014.
16. R. Kavuluru and A. Sabbir. Toward automated e-cigarette surveillance: Spotting e-cigarette proponents on Twitter. J. of biomedical informatics, 61:19-26, 2016.
17. S. Kiritchenko, X. Zhu, and S. M. Mohammad. Sentiment analysis of short informal texts. Journal of Artificial Intelligence Research, pages 723-762, 2014.
18. J. Landis and G. Koch. The measurement of observer agreement for categorical data. Biometrics, 33(1):159-174, 1977.
19. D. D. Luxton, J. D. June, and J. M. Fairall. Social media and suicide: a public health perspective. American Journal of Public Health, 102 (S2):S195-S200, 2012.
20. C. D. Manning, P. Raghavan, and H. Schütze. Introduction to Information Retrieval. Cambridge University Press, 2008.
21. E. Momeni, K. Tao, B. Haslhofer, and G.-J. Houben. Identification of useful user comments in social media: A case study on flickr commons. In Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL'13, pages 1-10. ACM, 2013.
22. National Library of Medicine. Unified Medical Language System Reference Manual. http://www.ncbi.nlm.nih.gov/books/NBK9676/.
23. M. Paul, A. Sarker, J. Brownstein, A. Nikfarjam, M. Scotch, K. Smith, and G. Gonzalez. Social media mining for public health monitoring and surveillance. In Pacific Symposium on Biocomputing., volume 21, pages 468-479, 2015.
24. F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825-2830, 2011.
25. Pew Research Center. Social media usage: 2005-2015. http://www.pewinternet.org/2015/10/08/social-networking-usage-2005-2015/.
26. M. Post and S. Bergsma. Explicit and implicit syntactic features for text classification. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, ACL 2013, Volume 2: Short Papers, pages 866-872, 2013.
27. A. Rios and R. Kavuluru. Convolutional neural networks for biomedical text classification: application in indexing biomedical articles. In Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics, pages 258-267. ACM, 2015.
28. A. Sarker, R. Ginn, A. Nikfarjam, K. O'Connor, K. Smith, S. Jayaraman, T. Upadhaya, and G. Gonzalez. Utilizing social media data for pharmacovigilance: a review. Journal of biomedical informatics, 54:202-212, 2015.
29. M. Surdeanu, T. Hicks, and M. A. Valenzuela-Escárcega. Two practical rhetorical structure theory parsers. In Proceedings of NAACL-HLT, pages 1-5, 2015.
30. M. Taboada and W. C. Mann. Applications of rhetorical structure theory. Discourse studies, 8(4):567-588, 2006.
31. M. Taboada and W. C. Mann. Rhetorical structure theory: Looking back and moving ahead. Discourse studies, 8(3):423-459, 2006.
32. Y. R. Tausczik and J. W. Pennebaker. The psychological meaning of words: Liwc and computerized text analysis methods. Journal of language and social psychology, 29(1):24-54, 2010.
33. S. Tuarob, C. S. Tucker, M. Salathe, and N. Ram. An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages. Journal of biomedical informatics, 49:255-268, 2014.
34. S. Wang and C. D. Manning. Baselines and bigrams: Simple, good sentiment and topic classification. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers-Volume 2, pages 90-94. Association for Computational Linguistics, 2012.
35. H.-H. Won, W. Myung, G.-Y. Song, W.-H. Lee, J.-W. Kim, B. J. Carroll, and D. K. Kim. Predicting national suicide numbers with social media data. PloS one, 8(4):e61809, 2013.
36. X. Yan and J. Han. gSpan: Graph-based substructure pattern mining. In Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), pages 721-724, 2002.