MaNLP@SMM4H’22: BERT for Classification of Twitter Posts

Keshav Kapur, Rajitha Harikrishnan, Sanjay Singh


Abstract
The reported work is our straightforward approach for the shared task “Classification of tweets self-reporting age” organized by the “Social Media Mining for Health Applications (SMM4H)” workshop. This literature describes the approach that was used to build a binary classification system, that classifies the tweets related to birthday posts into two classes namely, exact age(positive class) and non-exact age(negative class). We made two submissions with variations in the preprocessing of text which yielded F1 scores of 0.80 and 0.81 when evaluated by the organizers.
Anthology ID:
2022.smm4h-1.12
Volume:
Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Editors:
Graciela Gonzalez-Hernandez, Davy Weissenbacher
Venue:
SMM4H
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
42–43
Language:
URL:
https://aclanthology.org/2022.smm4h-1.12
DOI:
Bibkey:
Cite (ACL):
Keshav Kapur, Rajitha Harikrishnan, and Sanjay Singh. 2022. MaNLP@SMM4H’22: BERT for Classification of Twitter Posts. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 42–43, Gyeongju, Republic of Korea. Association for Computational Linguistics.
Cite (Informal):
MaNLP@SMM4H’22: BERT for Classification of Twitter Posts (Kapur et al., SMM4H 2022)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/2022.smm4h-1.12.pdf