Emoji Prediction in Tweets using BERT
- URL: http://arxiv.org/abs/2307.02054v3
- Date: Sat, 26 Aug 2023 11:02:16 GMT
- Title: Emoji Prediction in Tweets using BERT
- Authors: Muhammad Osama Nusrat, Zeeshan Habib, Mehreen Alam and Saad Ahmed
Jamal
- Abstract summary: We propose a transformer-based approach for emoji prediction using BERT, a widely-used pre-trained language model.
We fine-tuned BERT on a large corpus of text (tweets) containing both text and emojis to predict the most appropriate emoji for a given text.
Our experimental results demonstrate that our approach outperforms several state-of-the-art models in predicting emojis with an accuracy of over 75 percent.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In recent years, the use of emojis in social media has increased
dramatically, making them an important element in understanding online
communication. However, predicting the meaning of emojis in a given text is a
challenging task due to their ambiguous nature. In this study, we propose a
transformer-based approach for emoji prediction using BERT, a widely-used
pre-trained language model. We fine-tuned BERT on a large corpus of text
(tweets) containing both text and emojis to predict the most appropriate emoji
for a given text. Our experimental results demonstrate that our approach
outperforms several state-of-the-art models in predicting emojis with an
accuracy of over 75 percent. This work has potential applications in natural
language processing, sentiment analysis, and social media marketing.
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