Omar Benslimane
2023
NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation
Abdessamad Benlahbib
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Hamza Alami
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Achraf Boumhidi
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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.
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