DUTH at SemEval-2018 Task 2: Emoji Prediction in Tweets
Dimitrios Effrosynidis, Georgios Peikos, Symeon Symeonidis, Avi Arampatzis
Abstract
This paper describes the approach that was developed for SemEval 2018 Task 2 (Multilingual Emoji Prediction) by the DUTH Team. First, we employed a combination of pre-processing techniques to reduce the noise of tweets and produce a number of features. Then, we built several N-grams, to represent the combination of word and emojis. Finally, we trained our system with a tuned LinearSVC classifier. Our approach in the leaderboard ranked 18th amongst 48 teams.- Anthology ID:
- S18-1074
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 466–469
- Language:
- URL:
- https://aclanthology.org/S18-1074
- DOI:
- 10.18653/v1/S18-1074
- Cite (ACL):
- Dimitrios Effrosynidis, Georgios Peikos, Symeon Symeonidis, and Avi Arampatzis. 2018. DUTH at SemEval-2018 Task 2: Emoji Prediction in Tweets. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 466–469, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- DUTH at SemEval-2018 Task 2: Emoji Prediction in Tweets (Effrosynidis et al., SemEval 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/S18-1074.pdf