@inproceedings{kapur-etal-2022-manlp,
title = "{M}a{NLP}@{SMM}4{H}{'}22: {BERT} for Classification of {T}witter Posts",
author = "Kapur, Keshav and
Harikrishnan, Rajitha and
Singh, Sanjay",
editor = "Gonzalez-Hernandez, Graciela and
Weissenbacher, Davy",
booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {\&} Shared Task",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.smm4h-1.12",
pages = "42--43",
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.",
}
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%0 Conference Proceedings
%T MaNLP@SMM4H’22: BERT for Classification of Twitter Posts
%A Kapur, Keshav
%A Harikrishnan, Rajitha
%A Singh, Sanjay
%Y Gonzalez-Hernandez, Graciela
%Y Weissenbacher, Davy
%S Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F kapur-etal-2022-manlp
%X 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.
%U https://aclanthology.org/2022.smm4h-1.12
%P 42-43
Markdown (Informal)
[MaNLP@SMM4H’22: BERT for Classification of Twitter Posts](https://aclanthology.org/2022.smm4h-1.12) (Kapur et al., SMM4H 2022)
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.