@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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T NLP-LISAC at SemEval-2023 Task 12: Sentiment Analysis for Tweets expressed in African languages via Transformer-based Models
%A Benlahbib, Abdessamad
%A Boumhidi, Achraf
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F benlahbib-boumhidi-2023-nlp
%X 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.
%R 10.18653/v1/2023.semeval-1.28
%U https://aclanthology.org/2023.semeval-1.28
%U https://doi.org/10.18653/v1/2023.semeval-1.28
%P 199-204
Markdown (Informal)
[NLP-LISAC at SemEval-2023 Task 12: Sentiment Analysis for Tweets expressed in African languages via Transformer-based Models](https://aclanthology.org/2023.semeval-1.28) (Benlahbib & Boumhidi, SemEval 2023)
ACL