Лингвистический подход к определению суицида
https://doi.org/10.15514/ISPRAS-2014-26(4)-9
Аннотация
Об авторах
Л. М. ЕрмаковаРоссия
С. А. Ермаков
Россия
Список литературы
1. Wasserman, D., Cheng, Q., Jiang, G.X.: Global suicide rates among young people aged 15-19. World psychiatry. 4, pp. 114-120 (2005).
2. Paci, W.R.O.W. Towards Evidence-Based Suicide Prevention Programmes. World Health Organization, Western Pacific Region (2010).
3. SK: V Rossii rezko vozroslo chislo detskikh samoubijstv [Committee of inquiry: The number of children suicide dramatically increased in Russia], http//www.rg.ru/2012/10/24/deti.html. (in Russian)
4. World Health Organization: Preventing suicide : a resource for counsellors.
5. Gomez, D.D., Blasco-Fontecilla, H., Sukno, F., Ramos-Plasencia, M.S., Baca-Garcia, E. Suicide attempters classification: Toward predictive models of suicidal behavior. Neurocomputing. 92, pp. 3-8 (2012).
6. Early detection of depression and prevention of suicide, http://www.philstar.com/science-and-technology/147031/early-detection-depression-and-prevention-suicide.
7. Hjelmeland, H. Cultural Context Is Crucial in Suicide Research and Prevention, (2011).
8. Kostin, R.А., Shamkova, S.V. Suitsidy v molodezhnoj srede Sankt-Peterburga: sotsiologicheskij analiz [Suicide among the young people of Saint Petersburg: sociological analysis]. Sankt-Peterburgskij gos. universitet servisa i ehkonomiki [Saint-Petersburg state university of service and economy] (2007). (in Russian)
9. Pang, B., Lee, L. Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval. 2, pp. 1-135 (2008).
10. Jia, L., Yu, C.T., Meng, W. Improve the effectiveness of the opinion retrieval and opinion polarity classification. In: Shanahan, J.G., Amer-Yahia, S., Manolescu, I., Zhang, Y., Evans, D.A., Kolcz, A., Choi, K.-S., and Chowdhury, A. (eds.) CIKM. pp. 1415-1416. ACM (2008).
11. Eguchi, K., Lavrenko, V. Sentiment Retrieval using Generative Models. In: Jurafsky, D. and Gaussier, É. (eds.) EMNLP. pp. 345-354. ACL (2006).
12. Mukherjee, S., Bhattacharyya, P. Feature Specific Sentiment Analysis for Product Reviews. CoRR. abs/1209.2352, (2012).
13. Witten, I.H., Frank, E., Hall, M.A. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, Amsterdam (2011).
14. Chetviorkin, I.I., Loukachevitch, N.V. Sentiment analysis track at ROMI P 2012, (2013).
15. Ermakov, S., Ermakova, L. Sentiment Classification Based on Phonetic Characteristics. In: Serdyukov, P., Braslavski, P., Kuznetsov, S., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., and Yilmaz, E. (eds.) Advances in Information Retrieval. pp. 706-709. Springer Berlin Heidelberg (2013).
16. Chkhartishvili, G. Pisatel' i samoubijstvo.[Writers and suicide]. (2007). (in Russian)
17. Segalovich, I. A fast morphological algorithm with unknown word guessing induced by a dictionary for a web search engine. Proceedings of MLMTA. (2003).
18. Powers, D.M.W. Evaluation: From Precision, Recall and F-Factor to ROC, Informedness, Markedness & Correlation. School of Informatics and Engineering, Flinders University, Adelaide, Australia (2007).
19. Piao, S., Tsuruoka, Y., Ananiadou, S. Sentiment Analysis with Knowledge Resource and NLP Tools. The International Journal of Interdisciplinary Social Sciences. 4, pp. 17-28 (2012).
Рецензия
Для цитирования:
Ермакова Л.М., Ермаков С.А. Лингвистический подход к определению суицида. Труды Института системного программирования РАН. 2014;26(4):113-122. https://doi.org/10.15514/ISPRAS-2014-26(4)-9
For citation:
Ermakova L., Ermakov S. Linguistic Approach to Suicide Detection. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2014;26(4):113-122. (In Russ.) https://doi.org/10.15514/ISPRAS-2014-26(4)-9