Omar Benslimane
2023
NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation
Abdessamad Benlahbib | Hamza Alami | Achraf Boumhidi | Omar Benslimane
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Abdessamad Benlahbib | Hamza Alami | Achraf Boumhidi | Omar Benslimane
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
This paper presents our system and findings for SemEval 2023 Task 9 Tweet Intimacy Analysis. The main objective of this task was to predict the intimacy of tweets in 10 languages. Our submitted model (ranked 28/45) consists of a transformer-based approach with data augmentation via machine translation.