Analyzing Gender Polarity in Short Social Media Texts with BERT: The
Role of Emojis and Emoticons
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.
View on arXivComments on this paper
