Keywords

Suicidal behavior, cybersuicide, web mining, machine learning, deep learning, recurrent neural networks

Abstract

This article presents an Internet data analysis model based on Web Mining with the aim to find knowledge about large amounts of data in cyberspace. To test the proposed method, suicide web pages were analyzed as a study case to identify and detect traits in students with suicidal tendencies. The procedure considers a Web Scraper to locate and download information from the Internet, as well as Natural Language Processing techniques to retrieve the words. To explore the information, a dataset based on Dynamic Tables and Semantic Ontologies was constructed, specifying the predictive variables in young people with suicidal inclination. Finally, to evaluate the efficiency of the model, Machine Learning and Deep Learning algorithms were used. It should be noticed that the procedures for the construction of the dataset (using Genetic Algorithms) and obtaining the knowledge (using Parallel Computing and Acceleration with GPU) were optimized. The results reveal an accuracy of 96.28% on the detection of characteristics in adolescents with suicidal tendencies, reaching the best result through a Recurrent Neural Network with 98% accuracy. It is inferred that the model is viable to establish bases on mechanisms of action and prevention of suicidal behaviors, which can be implemented in educational institutions or different social actors.

View infography

References

Anggraini, I.Y, Sucipto, S., & Indriati, R. (2018). Cyberbullying detection modelling at Twitter social networking. Jurnal Informatika, 6(2), 113-118. https://doi.org/10.30595/juita.v6i2.3350

Link DOI | Link Google Scholar

Arevalos, D.H. (2020). El sentido de la vida y las prácticas ligadas al suicidio. Testimonio de jóvenes escolarizados. Revista Latinoamericana de Estudios sobre cuerpos, emociones y sociedad. 32(12), 52-63. https://bit.ly/3pXSVC8

Link Google Scholar

Beaven-Ciapara, N.I., Campa-Álvarez, R.A., Valenzuela, B.A., & Guillen-Lúgigo, M. (2018). Inclusión educativa: Factores psicosociales asociados a conducata suicida en adolescentes. Prisma Social, 23,185-207. https://bit.ly/3GRlO9X

Link Google Scholar

Berengueras, M. (2018). Suicidio la insoportable necesidad de ser otro. Universidad Autonoma del Estado de Morelos. https://bit.ly/3F7a8iW

Link Google Scholar

Blanco, C. (2019). El suicidio en España, respuesta institucional y social. Revista de Ciencias Sociales,33(46), 79-106. https://doi.org/10.26489/rvs.v33i46.5

Link DOI | Link Google Scholar

Bonami, B., Piazentini, L., & Dala-Possa, A. (2020). Education, Big Data and Artificial Intelligence: Mixed methods in digital platforms. [Educación, Big Data e Inteligencia Artificial: Metodologías mixtas en plataformas digitales]. Comunicar, 65, 43-52. https://doi.org/10.3916/C65-2020-04

Link DOI | Link Google Scholar

Carballo-Belloso, J.J., & Gómez-Peñalver, J. (2017). Relación entre bullying, autolesiones, ideación suicida e intentos auutoliticos en niños y adolescentes. Revista de estudios de Juventud, 115, 207-218. https://doi.org/10.3916/C65-2020-04

Link DOI | Link Google Scholar

Chiroma, F., Liu, H., & Cocea, M. (2018). Text Clasiffication For Suicide Related Tweets. International conference on Machine Learning and Cybernetics (ICMLC) (pp. 587-592). https://doi.org/10.1109/ICMLC.2018.8527039.

Link DOI | Link Google Scholar

Denia, E. (2020). The impact of science communication on Twitter: The case of Neil deGrasse Tyson. [El impacto del discurso científico en Twitter: El caso de Neil deGrasse Tyson]. Comunicar, 65, 21-30. https://doi.org/10.3916/C65-2020-02

Link DOI | Link Google Scholar

Du, J., Zhang, Y., Luo, J., Jia, Y., Wei, Qiang., Tao, C., & Xu, H.. (2018). Extracting psychiatric stressors for suicide from social media using deep learning. BMC Medical Informatics & Decision Making, 18(43), 77-87. https://doi.org/10.1186/s12911-018-0632-8

Link DOI | Link Google Scholar

Durkheim, E. (2008). El suicidio. Grupo Editorial Éxodo. https://bit.ly/3p6C8h7

Link Google Scholar

García-Peña, J.J. (Ed.) (2020). El suicidio: Una mirada integral e integradora. Universidad Católica Luis Amigó. https://doi.org/10.21501/9789588943619

Link DOI | Link Google Scholar

Gen-Min, L., Szu-Nian, Y., Yueh-Ming, T., et al. (2020). Machine Learning based suicide ideation prediction for military personnel. IEEE Journal of Biomedical and Healt Informatics, 24(7), 1907-1916.https://doi.org/10.1109/JBHI.2020.2988393

Link DOI | Link Google Scholar

Healy, M. (2019, June 21). Alcanzan máximo histórico los índices de suicidio de adolescentes y adultos jóvenes en EE.UU. Los Angeles Times. https://lat.ms/3IYhebO

Link Google Scholar

Hermosillo-De-la-Torre, A.E., Vacío-Muro, M.Á., Méndez-Sánchez, C., Palacios-Salas, P., & Sahagún-Padilla, Á.. (2015). Sintomatología depresiva, desesperanza y recursos psicológicos: una relación con tentativa de suicidio en una muestra de adolescentes mexicanos. Acta Universitaria 25(NE-2), 52-56. https://doi.org/10.15174/au.2015.900

Link DOI | Link Google Scholar

Kim, J., & Chung, K. (2019). Associative feature information extraction using text mining from health big data. Wireless Pers Commun, 105, 691-707. https://doi.org/10.1007/s11277-018-5722-5

Link DOI | Link Google Scholar

Landaeta G. (2014). Lista de stop words o palabras vacías en español. SEO para Google. https://bit.ly/3p2ysg3

Link Google Scholar

López-Martínez, L.F. (2020). Suicidio, adolescencia, redes sociales e Internet. Norte de salud mental, 17(63), 25-36. https://bit.ly/3sg25g2

Link Google Scholar

Luna, M., & Dávila, A. (2018). Adolescentes en riesgo: factores asociados con el intento de suicidio en México. Revista Gerencia y Política de Salud, 17(34), 1-14.: https://doi.org/10.11144/Javeriana.rgsp17-34.arfa

Link DOI | Link Google Scholar

Marchiori, H. (2015). El suicidio enfoque criminológico. Editorial Porrúa. https://bit.ly/3sfMYDu

Link Google Scholar

Molina, M.J., & Restrepo, D. (2018). Internet y comportamiento suicida en adolescentes: ¿Cuál es la conexión? Revista Pediatría, 51(2), 30-39. https://doi.org/10.14295/pediatr.v51i2.109

Link DOI | Link Google Scholar

Moreno, P., & Blanco, C. (2012). Suicidio e Internet. Medidas preventivas y de actuación. Revista Psiquiatria.com. 16(18). https://bit.ly/3E110Lb

Link Google Scholar

Mosquera, L. (2016). Conducta suicida en la infancia: Una revisión critica. Revista de Psicología Clínica con Niños y Adolescentes,3 9-18. https://bit.ly/3p5IkG8

Link Google Scholar

Nalini K., & Sheela L. (2014). A survey on Datamining in Cyber Bullying. International Journal on Recent and Innovation Trends in Computing and Communication,2 (7). https://bit.ly/3q7GHqt

Link Google Scholar

Olivares, S. (2019). Uso de Internet y conductas suicidas en adolescentes de 14 a 18 años en México. Visión criminológica-criminalística, 6-21. https://bit.ly/3p7uKSF

Link Google Scholar

Organización Mundial de la Salud (Ed.) (2019). Suicidio. Información obtenida el 6 de abril de 2021 en la dirección de Internet. OMS. https://bit.ly/3q8TkBG

Link Google Scholar

Pérez-Martínez, V.M., Aparicio-Vinacua, B., & Rodríguez-González, M.D. (2020). Acoso escolar, violación y suicidio en Twitter: Segunda temporada de «Por trece razones». Vivat Academia, 153, 137-168. https://doi.org/10.15178/va.2020.153.137-168

Link DOI | Link Google Scholar

Porter, M.F. (2006). An Algorithm for suffix stripping. Program: Electronic Library and Information Systems,40(3), 211-218. https://doi.org/10.1108/00330330610681286

Link DOI | Link Google Scholar

Ramírez-López, C.M., Montes, M., Ochoa-Zezzatti, A., Ponce-Gallegos, J.C., & Guzmán-Mendoza, J.E. (2021). Identification of possible suicide cases using a Bayesian Classifier with the database the Emergency Service 911 of Aguascalientes. International Journal of Combinatorial Optimization Problems and Informatics, 12(1), 43-57. https://bit.ly/32gamWt

Link Google Scholar

Rocamora, A. (2017). Cuando nada tiene sentido: Reflexiones sobre el suicidio desde la logoterapia. Editorial Desclée de Brouwer. https://bit.ly/3F9TxLa

Link Google Scholar

Roy, S.S., Mallik, A., Gulati, R., Obaidat, M.S., & Krishna, P.V. (2017). A deep learning based artificial neural network approach for intrusion detection. In D. Giri, R. Mohapatra, H. Begehr, & M. Obaidat (Eds.), Mathematics and Computing. ICMC 2017. Communications in Computer and Information Science, 655 (pp. 44-53). Springer. https://doi.org/10.1007/978-981-10-4642-1_5

Link DOI | Link Google Scholar

Sánchez-García., M.A, Pérez-de-Albéniz, A., Paíno, M., & Fonseca, P. (2018). Ajuste emocional y comportamental en una muestra de adolescentes españoles. Actas españolas de psiquiatria, 46(6), 205-216. https://bit.ly/3yAOv8a

Link Google Scholar

SeGob (Ed.) (2021). Impacto de la pandemia en niñas y niños. Secretaria de Gobernación de México. https://bit.ly/3J1bsGg

Link Google Scholar

Urra, J. (2019). La huella de la desesperanza: Estrategias de prevención y afrontamiento del suicidio. Ediciones Morata. https://bit.ly/30H1QiQ

Link Google Scholar

Villardón-Gallego, L. (2013). El pensamiento de suicidio en la adolescencia. Publicaciones de la Universidad de Deusto. https://bit.ly/33FtwFV

Link Google Scholar

Crossmark

Technical information

Received: 27-09-2021

Revised: 24-10-2021

Accepted: 03-12-2021

OnlineFirst: 01-02-2022

Publication date: 01-04-2022

Article revision time: 27 days | Average time revision issue 71: 45 days

Article acceptance time: 67 days | Average time of acceptance issue 71: 70 days

Preprint editing time: 141 days | Average editing time preprint issue 71: 144 days

Article editing time: 186 days | Average editing time issue 71: 189 days

Metrics

Metrics of this article

Views: 34776

Abstract readings: 32241

PDF downloads: 2535

Full metrics of Comunicar 71

Views: 375472

Abstract readings: 340406

PDF downloads: 35066

Cited by

Cites in Web of Science

Currently there are no citations to this document

Cites in Scopus

Durán-Mañes, Á., Paniagua-Rojano, F.-J., Fernández-Beltrán, F.. Analysis of media and audiences in social media facing information about suicide ), Comunicar, .

https://doi.org/10.3916/C77-2023-10

Cites in Google Scholar

La investigación educativa como didáctica en la enseñanza de la posverdad. Análisis de contextos AN Masegosa - Revista de Propuestas Educativas, 2023 - propuestaseducativas.org

https://propuestaseducativas.org/index.php/propuestas/article/view/1000

Download

Alternative metrics

How to cite

Castillo-Zúñiga, I., Luna-Rosas, F., & López-Veyna, J. (2022). Detection of traits in students with suicidal tendencies on Internet applying Web Mining. [Detección de rasgos en estudiantes con tendencia suicida en Internet aplicando Minería Web]. Comunicar, 71, 105-117. https://doi.org/10.3916/C71-2022-08

Share

           

Oxbridge Publishing House

4 White House Way

B91 1SE Sollihul United Kingdom

Administration

Editorial office

Creative Commons

This website uses cookies to obtain statistical data on the navigation of its users. If you continue to browse we consider that you accept its use. +info X