MINT ES

MINT, a new Multilingual intimacy analysis dataset covering 13,372 tweets in 10 languages including English, French, Spanish, Italian, Portuguese, Korean, Dutch, Chinese, Hindi, and Arabic. Tweets are annotated using a 1-5 likert scale.

Language(s)
Spanish
English
Dataset description link
https://codalab.lisn.upsaclay.fr/competitions/7096#participate
Year
2023
Domain
General
Text types
Tweets
Data access
Registration
Data link
https://codalab.lisn.upsaclay.fr/competitions/7096#participate
Publication
Jiaxin Pei, Vítor Silva, Maarten Bos, Yozen Liu, Leonardo Neves, David Jurgens, and Francesco Barbieri. 2023. SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 2235–2246, Toronto, Canada. Association for Computational Linguistics.
Publication link
https://aclanthology.org/2023.semeval-1.309.pdf
NLP Topic
modeling of intimacy
Number of units
1991
Type of units
Tweets
Size - additional information

intimacy level from 1 to 5

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.