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.
@article{arxiv.2301.05395,
title = {MaNLP@SMM4H22: BERT for Classification of Twitter Posts},
author = {Keshav Kapur and Rajitha Harikrishnan},
journal= {arXiv preprint arXiv:2301.05395},
year = {2023}
}