{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T17:23:59Z","timestamp":1742923439544,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031699818"},{"type":"electronic","value":"9783031699825"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-69982-5_9","type":"book-chapter","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T21:02:12Z","timestamp":1724965332000},"page":"110-123","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Self-harm Detection from Texts: A Comparative Study Utilizing BERT, Machine Learning, and Deep Learning Approaches"],"prefix":"10.1007","author":[{"given":"Rajalakshmi","family":"Sivanaiah","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sushmithaa","family":"Pandian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Subhankar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samyuktaa","family":"Sivakumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Rohan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Angel Deborah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,30]]},"reference":[{"issue":"3","key":"9_CR1","doi-asserted-by":"publisher","first-page":"57","DOI":"10.3390\/technologies10030057","volume":"10","author":"R Haque","year":"2022","unstructured":"Haque, R., et al.: A comparative analysis on suicidal ideation detection using NLP, machine, and deep learning. Technologies 10(3), 57 (2022)","journal-title":"Technologies"},{"key":"9_CR2","doi-asserted-by":"publisher","first-page":"117822261879286","DOI":"10.1177\/1178222618792860","volume":"10","author":"G Coppersmith","year":"2018","unstructured":"Coppersmith, G., Leary, R., Crutchley, P., Fine, A.: Natural language processing of social media as screening for suicide risk. Biomed. Inform. Insights 10, 117822261879286 (2018). https:\/\/doi.org\/10.1177\/1178222618792860","journal-title":"Biomed. Inform. Insights"},{"issue":"16","key":"9_CR3","doi-asserted-by":"publisher","first-page":"6351","DOI":"10.1016\/j.eswa.2013.05.050","volume":"40","author":"B Desmet","year":"2013","unstructured":"Desmet, B., Hoste, V.: Emotion detection in suicide notes. Expert Syst. Appl. 40(16), 6351\u20136358 (2013)","journal-title":"Expert Syst. Appl."},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Haque, F., et al.: A transformer-based approach to detect suicidal ideation using pre-trained language models. In: 2020 23rd International Conference on Computer and Information Technology (ICCIT). IEEE (2020)","DOI":"10.1109\/ICCIT51783.2020.9392692"},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Matero, M., et al.: Suicide risk assessment with multi-level dual-context language and BERT. In: Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology (2019)","DOI":"10.18653\/v1\/W19-3005"},{"key":"9_CR6","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/978-3-030-85251-1_15","volume-title":"CLEF 2021","author":"R Mart\u00ednez-Casta\u00f1o","year":"2021","unstructured":"Mart\u00ednez-Casta\u00f1o, R., Htait, A., Azzopardi, L., Moshfeghi, Y.: BERT-based transformers for early detection of mental health illnesses. In: Candan, K.S., et al. (eds.) CLEF 2021. LNCS, vol. 12880, pp. 189\u2013200. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-85251-1_15"},{"key":"9_CR7","unstructured":"Un Nisa, Q., Muhammad, R.: Towards transfer learning using BERT for early detection of self-harm of social media users. In: Proceedings of the Working Notes of CLEF, pp. 21\u201324 (2021)"},{"issue":"8","key":"9_CR8","doi-asserted-by":"publisher","first-page":"5789","DOI":"10.1007\/s10462-021-09958-2","volume":"54","author":"FA Acheampong","year":"2021","unstructured":"Acheampong, F.A., Nunoo-Mensah, H., Chen, W.: Transformer models for text-based emotion detection: a review of BERT-based approaches. Artif. Intell. Rev. 54(8), 5789\u20135829 (2021). https:\/\/doi.org\/10.1007\/s10462-021-09958-2","journal-title":"Artif. Intell. Rev."},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Ambalavanan, A.K., et al.: Using contextual representations for suicide risk assessment from Internet forums. In: Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology (2019)","DOI":"10.18653\/v1\/W19-3022"},{"key":"9_CR10","unstructured":"Kumar, A., Cambria, E., Trueman, T.E.: Transformer-based bidirectional encoder representations for emotion detection from text. In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE (2021)"},{"key":"9_CR11","series-title":"LNDECT","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/978-981-99-0741-0_27","volume-title":"DaSET 2022","author":"A Verma","year":"2023","unstructured":"Verma, A., et al.: Suicide ideation detection: a comparative study of sequential and transformer hybrid algorithms. In: Wah, Y.B., Berry, M.W., Mohamed, A., Al-Jumeily, D. (eds.) DaSET 2022. LNDECT, vol. 165, pp. 373\u2013387. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-99-0741-0_27"},{"issue":"16","key":"9_CR12","doi-asserted-by":"publisher","first-page":"10347","DOI":"10.3390\/ijerph191610347","volume":"19","author":"E Yeskuatov","year":"2022","unstructured":"Yeskuatov, E., Chua, S.-L., Foo, L.K.: Leveraging Reddit for suicidal ideation detection: a review of machine learning and natural language processing techniques. Int. J. Environ. Res. Public Health 19(16), 10347 (2022). https:\/\/doi.org\/10.3390\/ijerph191610347","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"9_CR13","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1016\/j.patrec.2023.02.016","volume":"167","author":"CM Greco","year":"2023","unstructured":"Greco, C.M., Simeri, A., Tagarelli, A., Zumpano, E.: Transformer-based language models for mental health issues: a survey. Pattern Recogn. Lett. 167, 204\u2013211 (2023). https:\/\/doi.org\/10.1016\/j.patrec.2023.02.016","journal-title":"Pattern Recogn. Lett."},{"key":"9_CR14","doi-asserted-by":"publisher","first-page":"109713","DOI":"10.1016\/j.asoc.2022.109713","volume":"130","author":"A Malhotra","year":"2022","unstructured":"Malhotra, A., Jindal, R.: Deep learning techniques for suicide and depression detection from online social media: a scoping review. Appl. Soft Comput. 130, 109713 (2022)","journal-title":"Appl. Soft Comput."},{"key":"9_CR15","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/978-94-015-9273-4_9","volume-title":"Syntactic Wordclass Tagging","author":"G Grefenstette","year":"1999","unstructured":"Grefenstette, G.: Tokenization. In: van Halteren, H. (ed.) Syntactic Wordclass Tagging, pp. 117\u2013133. Springer, Dordrecht (1999). https:\/\/doi.org\/10.1007\/978-94-015-9273-4_9"},{"key":"9_CR16","unstructured":"Devlin, J., et al.: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (2019)"},{"key":"9_CR17","unstructured":"https:\/\/www.theaidream.com\/post\/google-bert-understanding-the-architecture"},{"key":"9_CR18","unstructured":"https:\/\/www.kaggle.com\/datasets\/nikhileswarkomati\/suicide-watch"},{"key":"9_CR19","unstructured":"https:\/\/ncrb.gov.in\/uploads\/nationalcrimerecordsbureau\/custom\/adsiyeawise2022\/170161093707Chapter-2Suicides.pdf"},{"issue":"19","key":"9_CR20","doi-asserted-by":"publisher","first-page":"12635","DOI":"10.3390\/ijerph191912635","volume":"19","author":"THH Aldhyani","year":"2022","unstructured":"Aldhyani, T.H.H., Alsubari, S.N., Alshebami, A.S., Alkahtani, H., Ahmed, Z.A.T.: Detecting and analyzing suicidal ideation on social media using deep learning and machine learning models. Int. J. Environ. Res. Public Health 19(19), 12635 (2022). https:\/\/doi.org\/10.3390\/ijerph191912635","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"9_CR21","unstructured":"Gupta, S., Sinha, A.M., Prodhan, D., Ghosh, N., Modak, S.: Detecting depression and suicidal ideation from texts using machine learning & deep learning techniques. Department of Computer Science and Engineering, University Institute of Technology, The University of Burdwan, Golapbag (North), Burdwan-713104, West Bengal, India"},{"key":"9_CR22","doi-asserted-by":"publisher","first-page":"893","DOI":"10.3390\/app14020893","volume":"14","author":"H-S Choi","year":"2024","unstructured":"Choi, H.-S., Yang, J.: Innovative use of self-attention-based ensemble deep learning for suicide risk detection in social media posts. Appl. Sci. 14, 893 (2024). https:\/\/doi.org\/10.3390\/app14020893","journal-title":"Appl. Sci."}],"container-title":["IFIP Advances in Information and Communication Technology","Computational Intelligence in Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-69982-5_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T21:03:24Z","timestamp":1724965404000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-69982-5_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031699818","9783031699825"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-69982-5_9","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"30 August 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"We disclose that there is no conflict of interest regarding the contents of our findings, which have been thoroughly verified and stand independently of any other resource.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICCIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Intelligence in Data Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chennai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 February 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 February 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccids2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iccids.in","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}