Abstract
Emojis are a widely used tool for encoding emotional content in informal messages such as tweets,and predicting which emoji corresponds to a piece of text can be used as a proxy for measuring the emotional content in the text. This paper presents the first model for predicting emojis in highly multilingual text.Our BERTmoticon model is a fine-tuned version of the BERT model,and it can predict emojis for text written in 102 different languages.We trained our BERTmoticon model on 54.2 million geolocated tweets sent in the first 6 months of 2020,and we apply the model to a case study analyzing the emotional reaction of Twitter users to news about the coronavirus. Example findings include a spike in sadness when the World Health Organization (WHO) declared that coronavirus was a global pandemic, and a spike in anger and disgust when the number of COVID-19 related deaths in the United States surpassed one hundred thousand. We provide an easy-to-use and open source python library for predicting emojis with BERTmoticon so that the model can easily be applied to other data mining tasks.- Anthology ID:
- 2020.peoples-1.11
- Volume:
- Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Venue:
- PEOPLES
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 109–118
- Language:
- URL:
- https://aclanthology.org/2020.peoples-1.11
- DOI:
- Cite (ACL):
- Stefanos Stoikos and Mike Izbicki. 2020. Multilingual Emoticon Prediction of Tweets about COVID-19. In Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media, pages 109–118, Barcelona, Spain (Online). Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Emoticon Prediction of Tweets about COVID-19 (Stoikos & Izbicki, PEOPLES 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.peoples-1.11.pdf
- Code
- stefanos-stk/bertmoticon