# Emotion Analysis of Tweets Banning Education in Afghanistan

arXiv: https://arxiv.org/abs/2306.16268 · HTML: https://mlsanity.com/paper/2306.16268/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 23 references that are in the map.
- First posted on arXiv 28 Jun 2023.

## Builds on (most cited first, 5 of 5)

- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Learning Word Vectors for 157 Languages](https://mlsanity.com/paper/1802.06893/) (2018)
- [ParsBERT: Transformer-based Model for Persian Language Understanding](https://mlsanity.com/paper/2005.12515/) (2020)
- [SentiPers: A Sentiment Analysis Corpus for Persian](https://mlsanity.com/paper/1801.07737/) (2018)
- [ArmanEmo: A Persian Dataset for Text-based Emotion Detection](https://mlsanity.com/paper/2207.11808/) (2022)

## Built on by (most cited first, 2 of 2)

- [Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models](https://mlsanity.com/paper/2509.05719/) (2025)
- [Structural Stress and Learned Helplessness in Afghanistan: A Multi-Layer Analysis of the AFSTRESS Dari Corpus](https://mlsanity.com/paper/2603.27233/) (2026)

## Abstract (arXiv)

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.