Abstract
Despite being a fairly recent phenomenon, emojis have quickly become ubiquitous. Besides their extensive use in social media, they are now also invoked in customer surveys and feedback forms. Hence, there is a need for techniques to understand their sentiment and emotion. In this work, we provide a method to quantify the emotional association of basic emotions such as anger, fear, joy, and sadness for a set of emojis. We collect and process a unique corpus of 20 million emoji-centric tweets, such that we can capture rich emoji semantics using a comparably small dataset. We evaluate the induced emotion profiles of emojis with regard to their ability to predict word affect intensities as well as sentiment scores.- Anthology ID:
- R19-1126
- Volume:
- Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
- Month:
- September
- Year:
- 2019
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd.
- Note:
- Pages:
- 1094–1103
- Language:
- URL:
- https://aclanthology.org/R19-1126
- DOI:
- 10.26615/978-954-452-056-4_126
- Cite (ACL):
- Abu Awal Md Shoeb, Shahab Raji, and Gerard de Melo. 2019. EmoTag – Towards an Emotion-Based Analysis of Emojis. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 1094–1103, Varna, Bulgaria. INCOMA Ltd..
- Cite (Informal):
- EmoTag – Towards an Emotion-Based Analysis of Emojis (Shoeb et al., RANLP 2019)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/R19-1126.pdf