I2C-Huelva at SemEval-2023 Task 9: Analysis of Intimacy in Multilingual Tweets Using Resampling Methods and Transformers

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Abstract

Nowadays, intimacy is a fundamental aspect of how we relate to other people in social settings. The most frequent way in which we can determine a high level of intimacy is in the use of certain emoticons, curse words, verbs, etc. This paper presents the approach developed to solve SemEval 2023 task 9: Multiligual Tweet Intimacy Analysis. To address the task, a transfer learning approach was conducted by fine tuning various pre-trained languagemodels. Since the dataset supplied by the organizer was highly imbalanced, our main strategy to obtain high prediction values was the implementation of different oversampling and undersampling techniques on the training set. Our final submission achieved an overall Pearson’s r of 0.497.

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Pichardo Estevez, A., Mata Vázquez, J., Pachón Álvarez, V., & El Balima Cordero, N. (2023). I2C-Huelva at SemEval-2023 Task 9: Analysis of Intimacy in Multilingual Tweets Using Resampling Methods and Transformers. In Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023) (pp. 758–762). Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.semeval-1.104
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