Emotion Analysis of Tweets Banning Education in Afghanistan
This provides a resource for analyzing public sentiment in Dari, addressing a gap in low-resource language processing, though it is incremental as it applies existing methods to new data.
The paper introduces LetHerLearn, the first emotion-annotated dataset of 7,600 Dari tweets reacting to the Taliban's 2022 ban on women's education in Afghanistan, and benchmarks neural architectures for 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 ban of women rights to education in 2022 and has been manually annotated according to Ekman 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.