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Yozon Liu

SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis

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Oct 03, 2022
Jiaxin Pei, Vítor Silva, Maarten Bos, Yozon Liu, Leonardo Neves, David Jurgens, Francesco Barbieri
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We propose MINT, a new Multilingual INTimacy analysis dataset covering 13,384 tweets in 10 languages including English, French, Spanish, Italian, Portuguese, Korean, Dutch, Chinese, Hindi, and Arabic. We benchmarked a list of popular multilingual pre-trained language models. The dataset is released along with the SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis (https://sites.google.com/umich.edu/semeval-2023-tweet-intimacy).

* SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis 
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