@inproceedings{benlahbib-boumhidi-2023-nlp,
    title = "{NLP}-{LISAC} at {S}em{E}val-2023 Task 12: Sentiment Analysis for Tweets expressed in {A}frican languages via Transformer-based Models",
    author = "Benlahbib, Abdessamad  and
      Boumhidi, Achraf",
    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-1.28",
    doi = "10.18653/v1/2023.semeval-1.28",
    pages = "199--204",
    abstract = "This paper presents our systems and findings for SemEval-2023 Task 12: AfriSenti-SemEval: Sentiment Analysis for Low-resource African Languages. The main objective of this task was to determine the polarity of a tweet (positive, negative, or neutral). Our submitted models (highest rank is 1 and lowest rank is 21 depending on the target Track) consist of various Transformer-based approaches.",
}

This paper presents our systems and findings for SemEval-2023 Task 12: AfriSenti-SemEval: Sentiment Analysis for Low-resource African Languages. The main objective of this task was to determine the polarity of a tweet (positive, negative, or neutral). Our submitted models (highest rank is 1 and lowest rank is 21 depending on the target Track) consist of various Transformer-based approaches.
Benlahbib, Abdessamad Boumhidi, Achraf
NLP-LISAC at SemEval-2023 Task 12: Sentiment Analysis for Tweets expressed in African languages via Transformer-based Models