Enhanced word embeddings for anorexia nervosa detection on social media

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• dc.contributor.author Ramíırez-Cifuentes, Diana
• dc.contributor.author Largeron, Christine
• dc.contributor.author Tissier, Julien
• dc.contributor.author Freire, Ana
• dc.contributor.author Baeza Yates, Ricardo
• dc.date.accessioned 2020-04-28T10:14:28Z
• dc.date.available 2020-04-28T10:14:28Z
• dc.date.issued 2020
• dc.description Comunicació presentada a: The18th International Symposium on Intelligent Data Analysis, IDA 2020, celebrat del 27 al 29 d'abril de 2020 a Konstanz, Alemanya.ca
• dc.description.abstract Anorexia Nervosa (AN) is a serious mental disorder that has been proved to be traceable on social media through the analysis of users’ written posts. Here we present an approach to generate word embeddings enhanced for a classification task dedicated to the detection of Reddit users with AN. Our method extends Word2vec’s objective function in order to put closer domain-specific and semantically related words. The approach is evaluated through the calculation of an average similarity measure, and via the usage of the embeddings generated as features for the AN screening task. The results show that our method outperforms the usage of fine-tuned pre-learned word embeddings, related methods dedicated to generate domain adapted embeddings, as well as representations learned on the training set using Word2vec. This method can potentially be applied and evaluated on similar tasks that can be formalized as document categorization problems. Regarding our use case, we believe that this approach can contribute to the development of proper automated detection tools to alert and assist clinicians.en
• dc.description.sponsorship This work was supported by the University of Lyon - IDEXLYON and the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Program (MDM-2015-0502).
• dc.format.mimetype application/pdf
• dc.identifier.citation Ramírez-Cifuentes D, Largeron C, Tissier J, Freire A, Baeza-Yates R. Enhanced word embeddings for anorexia nervosa detection on social media. In: Berthold M, Feelders A, Krempl G, editors. Advances in Intelligent Data Analysis XVIII. 18th International Symposium on Intelligent Data Analysis, IDA 2020 Proceedings; 2020 Apr 27-29; Konstanz, Germany. Cham: Springer; 2020. p. 404-17. (LNCS; no. 12080). DOI: 10.1007/978-3-030-44584-3_32
• dc.identifier.doi http://dx.doi.org/10.1007/978-3-030-44584-3_32
• dc.identifier.isbn 978-3-030-44583-6
• dc.identifier.isbn 978-3-030-44584-3
• dc.identifier.issn 0302-9743
• dc.identifier.uri http://hdl.handle.net/10230/44357
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.ispartof Berthold M, Feelders A, Krempl G, editors. Advances in Intelligent Data Analysis XVIII. 18th International Symposium on Intelligent Data Analysis, IDA 2020 Proceedings; 2020 Apr 27-29; Konstanz, Germany. Cham: Springer; 2020. p. 404-17. (LNCS; no. 12080)
• dc.rights This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Social mediaen
• dc.subject.keyword Eating disordersen
• dc.subject.keyword Word embeddingsen
• dc.subject.keyword Anorexia nervosaen
• dc.subject.keyword Representation learningen
• dc.title Enhanced word embeddings for anorexia nervosa detection on social mediaen
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion