Abstract
This paper briefly describes our research groups' efforts in tackling Task 1 (Early Detection of Signs of Self-Harm), and Task 2 (Measuring the Severity of the Signs of Depression) from the CLEF eRisk Track. Core to how we approached these problems was the use of BERT-based classifiers which were trained specifically for each task. Our results on both tasks indicate that this approach delivers high performance across a series of measures, particularly for Task 1, where our submissions obtained the best performance for precision, F1, latency-weighted F1 and ERDE at 5 and 50. This work suggests that BERT-based classifiers, when trained appropriately, can accurately infer which social media users are at risk of self-harming, with precision up to 91.3% for Task 1. Given these promising results, it will be interesting to further refine the training regime, classifier and early detection scoring mechanism, as well as apply the same approach to other related tasks (e.g., anorexia, depression, suicide).
Original language | English |
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Title of host publication | Experimental IR Meets Multilinguality, Multimodality, and Interaction |
Subtitle of host publication | 12th International Conference of the CLEF Association, CLEF 2021, Proceedings |
Editors | K. Selçuk Candan, Bogdan Ionescu, Lorraine Goeuriot, Birger Larsen, Henning Müller, Alexis Joly, Maria Maistro, Florina Piroi, Guglielmo Faggioli, Nicola Ferro |
Place of Publication | Cham, Switzerland |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 189-200 |
Number of pages | 12 |
ISBN (Print) | 9783030852504 |
DOIs | |
Publication status | Published - 14 Sept 2021 |
Event | 12th International Conference of the Cross-Language Evaluation Forum for European Languages, CLEF 2021 - Virtual, Online Duration: 21 Sept 2021 → 24 Sept 2021 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12880 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 12th International Conference of the Cross-Language Evaluation Forum for European Languages, CLEF 2021 |
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City | Virtual, Online |
Period | 21/09/21 → 24/09/21 |
Funding
The first author would like to thank the following funding bodies for their support: FEDER/Ministerio de Ciencia, Innovaci?n y Universidades, Agencia Estatal de Investigaci?n/Project (RTI2018-093336-B-C21), Conseller?a de Educaci?n, Universidade e Formaci?n Profesional and the European Regional Development Fund (ERDF) (accreditation 2019?2022 ED431G-2019/04, ED431C 2018/29, ED431C 2018/19). The second and third authors would like to thank the UKRI?s EPSRC Project Cumulative Revelations in Personal Data (Grant Number: EP/R033897/1) for their support. We would also like to thank David Losada for arranging this collaboration. Acknowledgements. The first author would like to thank the following funding bodies for their support: FEDER/Ministerio de Ciencia, Innovación y Universidades, Agen-cia Estatal de Investigación/Project (RTI2018-093336-B-C21), Consellería de Edu-cación, Universidade e Formación Profesional and the European Regional Development Fund (ERDF) (accreditation 2019–2022 ED431G-2019/04, ED431C 2018/29, ED431C 2018/19). The second and third authors would like to thank the UKRI’s EPSRC Project Cumulative Revelations in Personal Data (Grant Number: EP/R033897/1) for their support. We would also like to thank David Losada for arranging this collaboration.
Keywords
- BERT
- classification
- depression
- early detection
- self-harm
- social media
- XLM-RoBERTa