Diseño, compilación y anotación de un corpus para la detección de mensajes suicidas en redes sociales

  1. Saray Zafra Cremades
  2. José M. Gómez Soriano
  3. Borja Navarro Colorado
Aldizkaria:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Argitalpen urtea: 2017

Zenbakia: 59

Orrialdeak: 65-72

Mota: Artikulua

DIALNET GOOGLE SCHOLAR lock_openRUA editor

Beste argitalpen batzuk: Procesamiento del lenguaje natural

Laburpena

In order to develop suicide prevention systems in the network, a pilot corpus of suicide thoughts was compiled and annotated. It was extracted from social networks. Texts has been obtained both from the Web and Deep Web. The selected written texts are in Spanish and English. Therefore, to characterize semantically each message, these have been annotated according to suicide relationship. The corpus compilation process ensures the representativeness of the texts and the consistent annotation between annotations.

Erreferentzia bibliografikoak

  • Alvarez Torres, S. M. 2012. Efecto Wert- ´ her: Una propuesta de intervención en la facultad de Ciencias Sociales y de la Comunicación (UPV/EHU). Norte de Salud Mental, (42):48–55.
  • Amini, P., H. Ahmadinia, J. Poorolajal, y M. Amiri Moqaddasi. 2016. Evaluating the High Risk Groups for Suicide: A Comparison of Logistic Regression, Support Vector Machine, Decision Tree and Artificial Neural Network. Iran J Public Health, 45(9):1179–1187.
  • Berk, M. y Dodd, H. S. 2006. The effect of macroeconomic variables on suicide. Psychol Med, 36(2):181–189.
  • Bonnyman, A. M., C. E. Webber, P. W. Stratford, y N. J. MacIntyre. 2012. Intrarater Reliability of Dual-Energy XRay Absorptiometry-Based Measures of Vertebral Height in Postmenopausal Women. Journal of Clinical Densitometry, 15(4):405–412, oct.
  • Bowker, Lynne y Pearson, J. 2002. Working with Specialized Language: A Practical Guide to Using Corpora. ComputerAided Translation Technology.
  • Cohen, J. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1):37–46, apr.
  • Cowie, J. y W. Lehnert. 1996. Information extraction. Communications of the ACM, 39(1):80–91, jan.
  • Cunningham, H., D. Maynard, K. Bontcheva, V. Tablan, N. Aswani, I. Roberts, G. Gorrell, A. Funk, A. Roberts, D. Damljanovic, T. Heitz, M. A. Greenwood, H. Saggion, J. Petrak, Y. Li, W. Peters, Dereczynski, y Leon. 2017. Developing Language Processing Components with GATE Version 8 (a User Guide).
  • De la Torre, M. 2013. Protocolo para la detección y atención inicial de la ideación suicida. Universidad Autónoma de Madrid, páginas 1–36.
  • Edelman, A. M. y S. L. Renshaw. 1982. Genuine versus simulated suicide notes: an issue revisited through discourse analysis. Suicide & life-threatening behavior, 12(2):103–13, jan.
  • Gleser, G. C., L. A. Gottschalk, y K. J. Springer. 1961. An anxiety scale applicable to verbal samples. Archives of general psychiatry, 5:593–605, dec.
  • Gould, M. S., D. Shaffer, y M. Kleinman. 1988. The Impact of Suicide in Television Movies: Replication and Commentary. Suicide and Life???Threatening Behavior, 18(1):90–99, sep.
  • Guan, L., B. Hao, Q. Cheng, P. S. Yip, y T. Zhu. 2015. Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model. JMIR mental health, 2(2):e17, may.
  • Huang, Y.-P., T. Goh, y C. L. Liew. 2007. Hunting Suicide Notes in Web 2.0 - Preliminary Findings. En Ninth IEEE International Symposium on Multimedia Workshops (ISMW 2007), páginas 517– 521. IEEE, dec.
  • Iliou, T., G. Konstantopoulou, M. Ntekouli, D. Lymberopoulos, K. Assimakopoulos, D. Galiatsatos, y G. Anastassopoulos. 2016. Machine Learning Preprocessing Method for Suicide Prediction. Springer, Cham, páginas 53–60.
  • INE. 2016. Encuesta sobre Equipamiento y Uso de Tecnologías de Información y Comunicación en los Hogares. Año 2016. página 1.
  • Kessler, R. C., G. Downey, J. R. Milavsky, y H. Stipp. 1988. Clustering of teenage suicides after television news stories about suicides: A reconsideration. American Journal of Psychiatry, 145(11):1379– 1383, sep.
  • Kessler, R. C., H. M. van Loo, K. J. Wardenaar, R. M. Bossarte, L. A. Brenner, T. Cai, D. D. Ebert, I. Hwang, J. Li, P. de Jonge, A. A. Nierenberg, M. V. Petukhova, A. J. Rosellini, N. A. Sampson, R. A. Schoevers, M. A. Wilcox, y A. M. Zaslavsky. 2016. Testing a machinelearning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports. Molecular Psychiatry, (October 2015):1–6. Diseño, compilación y anotación de un corpus para la detección de mensajes suicidas en redes sociales 71
  • Martinez Cámara, E., M. A. García Cumbreras, M. T. Martín Valdivia, y L. A. Ureña López. 2013. SINAI en TASS 2012. Procesamiento del Lenguaje Natural, 50:53– 60.
  • Martinez Cámara, E., M. T. Martín Valdivia, J. M. Perea Ortega, y L. A. Ureña López. 2011. Técnicas de clasificación de opiniones aplicadas a un corpus en español. Procesamiento del Lenguaje Natural, 47:163– 170.
  • Mchugh, M. L. 2012. Lessons in biostatistics Interrater reliability : the kappa statistic. páginas 276–282.
  • Mercy, J. A., M. J. Kresnow, P. W. O’Carroll, R. K. Lee, K. E. Powell, L. B. Potter, A. C. Swann, R. F. Frankowski, y T. L. Bayer. 2001. Is suicide contagious? A study of the relation between exposure to the suicidal behavior of others and nearly lethal suicide attempts. American Journal of Epidemiology, 154(2):120–127, jul.
  • Mok, K., A. M. Ross, A. F. Jorm, y J. Pirkis. 2016. An Analysis of the Content and Availability of Information on Suicide Methods Online. Journal of Consumer Health on the Internet, 20(1-2):41–51, apr.
  • Mowery, D., H. A. Smith, T. Cheney, C. Bryan, y M. Conway. 2016. Identifying Depression-Related Tweets from Twitter for Public Health Monitoring. Online Journal of Public Health Informatics, 8(1), mar.
  • Nguyen, T., T. Tran, S. Gopakumar, D. Phung, y S. Venkatesh. 2016. An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments. páginas 1–29.
  • Osgood, C. E. y E. G. Walker. 1959. Motivation and language behavior: a content analysis of suicide notes. Journal of abnormal psychology, 59(1):58–67, jul.
  • Pang, B. y L. Lee. 2008. Opinion Mining and Sentiment Analysis. Foundations and Trends R in Information Retrieval, 2(1–2):1–135, jan.
  • Pennebaker, J. W. y C. K. Chung. 2011. Expressive Writing, Emotional Upheavals, and Health. En Howard S. Friedman, editor, Expressive Writing, Emotional Upheavals, and Health. Oxford University Press, capítulo 18, página 936.
  • Pestian, J., H. Nasrallah, Matykiewicz, A. Bennett, y A. Leenaars. 2010. Suicide Note Classification Using Natural Language Processing. Biomed Inform Insights, 3:19–28.
  • Pestian, J. P., P. Matykiewicz, M. Linn-Gust, B. South, O. Uzuner, J. Wiebe, K. B. Cohen, J. Hurdle, y C. Brew. 2012. Sentiment Analysis of Suicide Notes: A Shared Task. Biomedical informatics insights, 5(Suppl 1):3–16, jan.
  • Pestian, J. P., M. Sorter, B. Connolly, K. B. Cohen, J. T. Gee, L.-p. Morency, y S. Scherer. 2016. A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects : A Prospective Multicenter Trial. The American Association of Suicidiology, páginas 1–10.
  • Salton, G. y M. J. McGill. 1986. Introduction to Modern Information Retrieval. McGraw-Hill, Inc., oct.
  • Schwartz, H. A., J. Eichstaedt, M. L. Kern, G. Park, M. Sap, D. Stillwell, M. Kosinski, y L. Ungar. 2014. Towards Assessing Changes in Degree of Depression through Facebook. En Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, páginas 118– 125, Baltimore. Association for Computational Linguistics.
  • Sebastiani, F. 2002. Machine learning in automated text categorization. ACM Computing Surveys, 34(1):1–47, mar.
  • Shneidman, E. S. y N. L. Farberow. 1956. Clues to suicide. Public health reports, 71(2):109–14, feb.
  • Wasserman, D., E. Mittendorfer Rutz, W. Rutz, y A. Schmidtke. 2004. Suicide Prevention In Europe. Informe técnico, National and Stockholm County Council’s Centre for Suicide Research and Prevention of Mental Ill-Health.
  • WHO. 2014. Preventing suicide: A global imperative. Informe técnico, World Health Organization.
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