Multilingual Emoticon Prediction of Tweets about COVID-19

Stefanos Stoikos, Mike Izbicki


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:
Bibkey:
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)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.peoples-1.11.pdf
Code
 stefanos-stk/bertmoticon