Datasets › ArmanEmo

ArmanEmo

Introduced by Hossein Mirzaee et al. in ArmanEmo: A Persian Dataset for Text-based Emotion Detection24 Jul 2022 archive 2025-07-28

ArmanEmo is a human-labeled emotion dataset of more than 7000 Persian sentences labeled for seven categories. The dataset has been collected from different resources, including Twitter, Instagram, and Digikala (an Iranian e-commerce company) comments. Labels are based on Ekman's six basic emotions (Anger, Fear, Happiness, Hatred, Sadness, Wonder) and another category (Other) to consider any other emotion not included in Ekman's model.

Source: ArmanEmo: A Persian Dataset for Text-based Emotion Detection

Image Source: https://arxiv.org/pdf/2207.11808v1.pdf

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Emotion Classification ArmanEmo Deep ParsBERT Macro F1 0.65 Investigating Shallow and Deep Learning Techniques for... vkiani/ShortPersianEmo 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 6. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian Texts 1 1 16 Dec 2023 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

Creative Commons Attribution 4.0 International

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • ArmanEmo

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections