Cordyceps@LT-EDI : Depression Detection with Reddit and Self-training

Dean Ninalga


Abstract
Depression is debilitating, and not uncommon. Indeed, studies of excessive social media users show correlations with depression, ADHD, and other mental health concerns. Given that there is a large number of people with excessive social media usage, then there is a significant population of potentially undiagnosed users and posts that they create. In this paper, we propose a depression detection system using a semi-supervised learning technique. Namely, we use a trained model to classify a large number of unlabelled social media posts from Reddit, then use these generated labels to train a more powerful classifier. We demonstrate our framework on Detecting Signs of Depression from Social Media Text - LT-EDI@RANLP 2023 shared task, where our framework ranks 3rd overall.
Anthology ID:
2023.ltedi-1.29
Volume:
Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion
Month:
September
Year:
2023
Address:
Varna, Bulgaria
Editors:
Bharathi R. Chakravarthi, B. Bharathi, Joephine Griffith, Kalika Bali, Paul Buitelaar
Venues:
LTEDI | WS
SIG:
Publisher:
INCOMA Ltd., Shoumen, Bulgaria
Note:
Pages:
192–197
Language:
URL:
https://aclanthology.org/2023.ltedi-1.29
DOI:
Bibkey:
Cite (ACL):
Dean Ninalga. 2023. Cordyceps@LT-EDI : Depression Detection with Reddit and Self-training. In Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion, pages 192–197, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):
Cordyceps@LT-EDI : Depression Detection with Reddit and Self-training (Ninalga, LTEDI-WS 2023)
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PDF:
https://aclanthology.org/2023.ltedi-1.29.pdf