Emotion Analysis of Tweets Banning Education in Afghanistan

TL;DR

This paper presents a new emotion-annotated dataset of Dari tweets reacting to Afghanistan's education ban, and benchmarks neural models for emotion classification in this context.

Contribution

It introduces the first Dari emotion dataset related to a specific socio-political event and evaluates neural models for emotion detection in this language and setting.

Findings

Neural models achieve moderate accuracy on Dari emotion classification.

The dataset contains 7,600 manually annotated tweets.

Initial experiments establish baseline performance for future research.

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 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.