@inproceedings{l-etal-2023-interns,
title = "Interns@{LT}-{EDI} : Detecting Signs of Depression from Social Media Text",
author = "L, Koushik and
L, Hariharan R. and
M, Anand Kumar",
editor = "Chakravarthi, Bharathi R. and
Bharathi, B. and
Griffith, Joephine and
Bali, Kalika and
Buitelaar, Paul",
booktitle = "Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.ltedi-1.40",
pages = "262--265",
abstract = "This submission presents our approach for depression detection in social media text. The methodology includes data collection, preprocessing - SMOTE, feature extraction/selection - TF-IDF and Glove, model development- SVM, CNN and Bi-LSTM, training, evaluation, optimisation, and validation. The proposed methodology aims to contribute to the accurate detection of depression.",
}
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<abstract>This submission presents our approach for depression detection in social media text. The methodology includes data collection, preprocessing - SMOTE, feature extraction/selection - TF-IDF and Glove, model development- SVM, CNN and Bi-LSTM, training, evaluation, optimisation, and validation. The proposed methodology aims to contribute to the accurate detection of depression.</abstract>
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%0 Conference Proceedings
%T Interns@LT-EDI : Detecting Signs of Depression from Social Media Text
%A L, Koushik
%A L, Hariharan R.
%A M, Anand Kumar
%Y Chakravarthi, Bharathi R.
%Y Bharathi, B.
%Y Griffith, Joephine
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F l-etal-2023-interns
%X This submission presents our approach for depression detection in social media text. The methodology includes data collection, preprocessing - SMOTE, feature extraction/selection - TF-IDF and Glove, model development- SVM, CNN and Bi-LSTM, training, evaluation, optimisation, and validation. The proposed methodology aims to contribute to the accurate detection of depression.
%U https://aclanthology.org/2023.ltedi-1.40
%P 262-265
Markdown (Informal)
[Interns@LT-EDI : Detecting Signs of Depression from Social Media Text](https://aclanthology.org/2023.ltedi-1.40) (L et al., LTEDI-WS 2023)
ACL