NLP-LISAC at SemEval-2023 Task 12: Sentiment Analysis for Tweets expressed in African languages via Transformer-based Models

24941

Authors

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Abstract

AbstractThis 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.

Keywords

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Full Content

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Labeled Text

AbstractThis 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.

Publication Details

Paper ID:
24941
Year:
2023
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan