The Unveiling Distress: Harnessing NLP and Deep Learning to Identify Suicidal Signals in Tweets
DOI:
https://doi.org/10.54489/ymy5bp91Keywords:
Suicidal Signals, NLP, Twitter, Deep Learning, Mental HealthAbstract
The rise of social media platforms has provided researchers with unprecedented access to vast amounts of user-generated content, offering a unique opportunity to explore various aspects of human behavior, including mental health. This paper presents a novel approach to identifying suicidal signals in tweets using Natural Language Processing (NLP) techniques and Deep Learning algorithms. We propose a multi-step methodology that involves data collection, preprocessing, feature extraction, and classification. Leveraging state-of-the-art deep learning architectures such as recurrent neural networks (RNNs) and transformer models, our approach aims to accurately detect linguistic patterns indicative of suicidal ideation and distress. We evaluate the effectiveness of our method using a large dataset of annotated tweets and demonstrate promising results in terms of both precision and recall. Furthermore, we discuss the ethical implications and potential applications of our research in suicide prevention and mental health support systems.
References
E. R. Kumar and N. Venkatram, ‘‘Predicting and analyzing suicidal risk behavior using rule-based approach in Twitter data,’’ Soft Comput., pp. 1–9, 2023.
A.Raza,F.Rustam,H.U.R.Siddiqui,I.D.L.T.Diez,B.Garcia-Zapirain, E. Lee, and I. Ashraf, ‘‘Predicting genetic disorder and types of disorder using chain classifier approach,’’ Genes, vol. 14, no. 1, p. 71, Dec. 2022.
Suicide. Available online: https://www.who.int/news-room/fact-sheets/detail/suicide (accessed on 27 September 2021).
Ivey-Stephenson, A.Z.; Demissie, Z.; Crosby, A.E.; Stone, D.M.; Gaylor, E.; Wilkins, N.; Lowry, R.; Brown, M. Suicidal Ideation and Behaviors Among High School Students—Youth Risk Behavior Survey, United States, 2019. MMWR Suppl. 2020, 69, 47–55. [Google Scholar] [CrossRef] [PubMed]
Gliatto, M.F.; Rai, A.K. Evaluation and Treatment of Patients with Suicidal Ideation. Am. Fam. Physician 1999, 59, 1500. [Google Scholar] [PubMed]
D. De Berardis, G. Martinotti, and M. Di Giannantonio, ‘‘Understanding the complex phenomenon of suicide: From research to clinical practice,’’ Frontiers Psychiatry, vol. 9, p. 61, 2018.
Z. Li, J. Zhou, Z. An, W. Cheng, and B. Hu, ‘‘Deep hierarchical ensemble model for suicide detection on imbalanced social media data,’’ Entropy, vol. 24, no. 4, p. 442, Mar. 2022.
D. Kodati and R. Tene, ‘‘Identifying suicidal emotions on social media through transformer-based deep learning,’’ Appl. Intell., vol. 53, no. 10, pp. 11885–11917, 2023.
J. C. Franklin, J. D. Ribeiro, K. R. Fox, K. H. Bentley, E. M. Kleiman, X. Huang, K. M. Musacchio, A. C. Jaroszewski, B. P. Chang, and M. K. Nock, ‘‘Risk factors for suicidal thoughts and behaviors: A metaanalysis of 50 years of research,’’ Psychol. Bull., vol. 143, no. 2, pp. 187–232, 2017.
K. H. Bentley, J. C. Franklin, J. D. Ribeiro, E. M. Kleiman, K. R. Fox, and M. K. Nock, ‘‘Anxiety and its disorders as risk factors for suicidal thoughts and behaviors: A meta-analytic review,’’ Clin. Psychol. Rev., vol. 43, pp. 30–46, Feb. 2016.
L. Orsolini, R. Latini, M. Pompili, G. Serafini, U. Volpe, F. Vellante, M. Fornaro, A. Valchera, C. Tomasetti, S. Fraticelli, M. Alessandrini, R. La Rovere, S. Trotta, G. Martinotti, M. Di Giannantonio, and D. De Berardis, ‘‘Understanding the complex of suicide in depression: From research to clinics,’’ Psychiatry Invest., vol. 17, no. 3, pp. 207–221, Mar. 2020.
N. H. Kalin, ‘‘Insights into suicide and depression,’’ Amer. J. Psychiatry, vol. 177, no. 10, pp. 877–880, Oct. 2020.
L. da Silva Costa, Á. P. Alencar, P. N. Neto, M. do Socorro Vieira dos Santos, C. G. L. da Silva, S. de França Lacerda Pinheiro, R. T. Silveira, B. A. V. Bianco, R. F. F. P. Júnior, M. A. P. de Lima, A. O. A. Reis, and M. L. R. Neto, ‘‘Risk factors for suicide in bipolar disorder: A systematic review,’’ J. Affect. Disorders, vol. 170, pp. 237–254, Jan. 2015.
J.Paris,‘‘Suicidality in borderline personality disorder,’’Medicina,vol.55, no. 6, p. 223, May 2019.
K. H. Lee, J. S. Jun, Y. J. Kim, S. Roh, S. S. Moon, N. Bukonda, and L. Hines, ‘‘Mental health, substance abuse, and suicide among homeless adults,’’ J. Evidence-Informed Social Work, vol. 14, no. 4, pp. 229–242, Jul. 2017.
N. Leigh-Hunt, D. Bagguley, K. Bash, V. Turner, S. Turnbull, N. Valtorta, and W. Caan, ‘‘An overview of systematic reviews on the public health consequences of social isolation and loneliness,’’ Public Health, vol. 152, pp. 157–171, Nov. 2017.
J. Holt-Lunstad, T. B. Smith, M. Baker, T. Harris, and D. Stephenson, ‘‘Loneliness and social isolation as risk factors for mortality: A metaanalytic review,’’ Perspect. Psychol. Sci., vol. 10, no. 2, pp. 227–237, Mar. 2015.
A. Allchin, V. Chaplin, and J. Horwitz, ‘‘Limiting access to lethal means: Applying the social ecological model for firearm suicide prevention,’’ Injury Prevention, vol. 25, no. 1, pp. i44–i48, Sep. 2019.
K.A.V.Orden,TK.Witte,K.C.Cukrowicz,S.R.Braithwaite,E.A.Selby, and T. E. Joiner Jr., ‘‘The interpersonal theory of suicide,’’ Psychol. Rev., vol. 117, no. 2, pp. 575–600, 2010.
A.WenzelandA.T.Beck,‘‘Acognitivemodelofsuicidalbehavior:Theory and treatment,’’ Appl. Preventive Psychol., vol. 12, no. 4, pp. 189–201, Oct. 2008.
R.J.CramerandN.D.Kapusta,‘‘Asocial-ecologicalframeworkoftheory, assessment,andpreventionofsuicide,’’FrontiersPsychol.,vol.8,p. 1756, Oct. 2017.
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