Parapar, J. orcid.org/0000-0002-5997-8252, Perez, A. orcid.org/0000-0002-0480-006X, Wang, X. orcid.org/0000-0001-5936-9919 et al. (1 more author) (2025) eRisk 2025: contextual and conversational approaches for depression challenges. In: Hauff, C., Macdonald, C., Jannach, D., Kazai, G., Nardini, F.M., Pinelli, F., Silvestri, F. and Tonellotto, N., (eds.) Advances in Information Retrieval: 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6–10, 2025, Proceedings, Part V. 47th European Conference on Information Retrieval, ECIR 2025, 06-10 Apr 2025, Lucca, Italy. Lecture Notes in Computer Science (LNCS 15576). Springer Nature Switzerland , pp. 416-424. ISBN 9783031887192
Abstract
Since its foundation in 2017, the eRisk CLEF Lab has pioneered research in early risk detection on the Internet, focusing on various mental health challenges such as depression, anorexia, and pathological gambling. Over the years, participants have contributed importantly to the development of detection models and exploited the datasets we created to address these critical disorders. In 2025, for the ninth edition of the lab, we introduce new tasks designed to improve risk detection actual approaches through deeper contextual and conversational analysis. This year’s eRisk lab includes the continuation of the sentence ranking task for depressive symptoms, along with two new tasks: contextualized early detection of depression, which leverages full conversational interactions, and a pilot task on detecting depression using fine-tuned conversational agents. This paper outlines our progress to date, shares insights from previous editions, and details our innovative plans for eRisk 2025.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Advances in Information Retrieval is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Information and Computing Sciences; Human-Centred Computing; Clinical Research; Depression; Mental Health; Mental Illness; Behavioral and Social Science; Prevention; Brain Disorders; Mental health |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Apr 2025 07:42 |
Last Modified: | 19 Apr 2025 21:33 |
Status: | Published |
Publisher: | Springer Nature Switzerland |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-031-88720-8_62 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:225607 |