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

2024-06-13 · Saba Yousefian Jazi, Amir Mirzaeinia, Sina Yousefian Jazi

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.

📄 PDF Abstract BibTeX arXiv:2406.09573

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Attention Dropout Attention Dropout is a type of dropout used in attention-based architectures, where elements are randomly dropped out of the…
Linear Warmup With Linear Decay Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.
Weight Decay 설명 없음
Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…
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Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

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