@inproceedings{hussiny-ovrelid-2023-emotion,
    title = "Emotion Analysis of Tweets Banning Education in {A}fghanistan",
    author = "Hussiny, Mohammad Ali  and
      {\O}vrelid, Lilja",
    editor = "Barnes, Jeremy  and
      De Clercq, Orph{\'e}e  and
      Klinger, Roman",
    booktitle = "Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.wassa-1.24",
    doi = "10.18653/v1/2023.wassa-1.24",
    pages = "271--277",
    abstract = "This paper introduces the first emotion-annotated dataset for the Dari variant of Persian spoken in Afghanistan. The LetHerLearn dataset contains 7,600 tweets posted in reaction to the Taliban{'}s ban of women{'}s rights to education in 2022 and has been manually annotated according to Ekman{'}s emotion categories. We here detail the data collection and annotation process, present relevant dataset statistics as well as initial experiments on the resulting dataset, benchmarking a number of different neural architectures for the task of Dari emotion classification.",
}

This paper introduces the first emotion-annotated dataset for the Dari variant of Persian spoken in Afghanistan. The LetHerLearn dataset contains 7,600 tweets posted in reaction to the Taliban{'}s ban of women{'}s rights to education in 2022 and has been manually annotated according to Ekman{'}s emotion categories. We here detail the data collection and annotation process, present relevant dataset statistics as well as initial experiments on the resulting dataset, benchmarking a number of different neural architectures for the task of Dari emotion classification.
Hussiny, Mohammad Ali {\O}vrelid, Lilja
Emotion Analysis of Tweets Banning Education in Afghanistan