Abstract
Emoji (digital pictograms) are crucial features for textual sentiment analysis. However, analysing the sentiment roles of emoji is very complex. This is due to its dependency on different factors, such as textual context, cultural perspective, interlocutor’s personal traits, interlocutors’ relationships or a platforms’ functional features. This work introduces an approach to analysing the sentiment effects of emoji as textual features. Using an Arabic dataset as a benchmark, our results confirm the borrowed argument that each emoji has three different norms of sentiment role (negative, neutral or positive). Therefore, an emoji can play different sentiment roles depending upon the context. It can behave as an emphasizer, an indicator, a mitigator, a reverser or a trigger of either negative or positive sentiment within a text. In addition, an emoji may have a neutral effect (i.e., no effect) on the sentiment of the text.- Anthology ID:
- 2022.wanlp-1.32
- Volume:
- Proceedings of the The Seventh Arabic Natural Language Processing Workshop (WANLP)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 346–355
- Language:
- URL:
- https://aclanthology.org/2022.wanlp-1.32
- DOI:
- Cite (ACL):
- Shatha Ali A. Hakami, Robert Hendley, and Phillip Smith. 2022. Emoji Sentiment Roles for Sentiment Analysis: A Case Study in Arabic Texts. In Proceedings of the The Seventh Arabic Natural Language Processing Workshop (WANLP), pages 346–355, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Emoji Sentiment Roles for Sentiment Analysis: A Case Study in Arabic Texts (Hakami et al., WANLP 2022)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2022.wanlp-1.32.pdf