Analyzing Gender Polarity in Short Social Media Texts with BERT: The Role of Emojis and Emoticons

arXiv:2406.09573v1 Announce Type: new
Abstract: In this effort we fine tuned different models based on BERT to detect the gender polarity of twitter accounts. We specially focused on analyzing the effect of using emojis and emoticons in performance of our model in classifying task. We were able to demonstrate that the use of these none word inputs alongside the mention of other accounts in a short text format like tweet has an impact in detecting the account holder’s gender.



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