TechWhiz@LT-EDI-2023: Transformer Models to Detect Levels of Depression from Social Media Text

Madhumitha M, Jerin Mahibha C, Thenmozhi D.

Abstract
Depression is a mental fitness disorder from persistent reactions of unhappiness, void, and a deficit of interest in activities. It can influence differing facets of one’s life, containing their hopes, sympathy, and nature. Depression can stem from a sort of determinant, in the way that ancestral willingness, life occurrences, and social circumstances. In current years, the influence of social media on mental fitness has become an increasing concern. Excessive use of social media and the negative facets that guide it, can exacerbate or cause impressions of distress. The nonstop exposure to cautiously curated lives, social comparison, cyberbullying, and the pressure to meet unreal standards can impact an individual’s pride, social connections, and overall well-being. We participated in the shared task at DepSignLT-EDI@RANLP 2023 and have proposed a model that identifies the levels of depression from social media text using the data set shared for the task. Different transformer models like ALBERT and RoBERTa are used by the proposed model for implementing the task. The macro F1 score obtained by ALBERT model and RoBERTa model are 0.258 and 0.143 respectively.
Anthology ID:
2023.ltedi-1.30
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:
198–203
Language:
URL:
https://aclanthology.org/2023.ltedi-1.30
DOI:
Bibkey:
Cite (ACL):
Madhumitha M, Jerin Mahibha C, and Thenmozhi D.. 2023. TechWhiz@LT-EDI-2023: Transformer Models to Detect Levels of Depression from Social Media Text. In Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion, pages 198–203, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):
TechWhiz@LT-EDI-2023: Transformer Models to Detect Levels of Depression from Social Media Text (M et al., LTEDI-WS 2023)
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