@inproceedings{benlahbib-etal-2023-nlp,
    title = "{NLP}-{LISAC} at {S}em{E}val-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation",
    author = "Benlahbib, Abdessamad  and
      Alami, Hamza  and
      Boumhidi, Achraf  and
      Benslimane, Omar",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.semeval-1.16",
    doi = "10.18653/v1/2023.semeval-1.16",
    pages = "121--124",
    abstract = "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.",
}

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