| DataSet | Type | Classes | # Classes | # Samples | Domains | EmotionModel | Year | License | paper |
|---|---|---|---|---|---|---|---|---|---|
| ShortPersianEmo | Emotion | happiness:1625, sadness:939, anger:1125, fear:380, and other:1403 | 5 | 5472 | Twitter, Digikala | RachaelJack | 2023 | GNU | Investigating shallow and deep learning techniques for emotion classification in short Persian texts |
| JAMFA | Emotion | Anger/Disgust, Happiness, Fear/Surprise, Sadness | 4 | 2241 | Fiction | EKMAN | 2022 | --- | Deep Emotion Detection Sentiment Analysis of Persian Literary Text |
| PersianTweets | Emotion | Anger:20069, Disgust:925, joy:28024, Fear:17624, Surprise:12859, Sadness:34328 | 6 | 113829 | EKMAN | 2021 | Author's permission | - | |
| ArmanEmo | Emotion | Anger:1077, Fear:814, Happiness:893, Hatred:576, Sadness:1158, Wonder:884, Other:1874 | 7 | 7308 | Twitter, Instagram, and Digikala | EKMAN | 2022 | non-commercial use | - |
| EmoPars | Emotion | Anger:1632, Fear:690, Happiness:692, Sadness:1770, Hatred:1256, Wonder:986 | 6 | 29997 | EKMAN | 2021 | not specified | - |
| DataSet | # Classes | # Samples | Domains | Year | License | Paper Title | Notes |
|---|---|---|---|---|---|---|---|
| Not specified | 3 | 12055 | 2021 | - | ParsBERT Post-Training for Sentiment Analysis of Tweets Concerning Stock Market | - | |
| JAMFA | 2 | 2241 | Fiction | 2022 | Author's permission | Deep Emotion Detection Sentiment Analysis of Persian Literary Text | - |
| Pars-ABSA | 1:5114, 0:1827, -1:3061 | 10002 | Digikala | 2022 | not specified | Pars-ABSA: a Manually Annotated Aspect-based Sentiment Analysis Benchmark on Farsi Product Reviews | Aspect based |
| Snappfood | 1:35000, 0:35000 | 70000 | Snappfood | 2022 | not specified | - | - |
| DeepSentiPers | 2:988, 1:1623, 0:2409, -1:513, -2:28 | 19550 | Digikala | 2020 | not specified | DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus | - |
| Product reviews dataset | 2 | 3000 | Digikala | 2018 | not specified | Words are important: Improving sentiment analysis in the persian language by lexicon refining | - |
| Hotel reviews dataset | 2 | 3600 | hellokish | 2015 | not specified | Opinion Mining in Persian Language Using Supervised Algorithms | - |
| Not specified | 2 | 8373 | Sahamyab | 2019 | not specified | Tehran Stock Exchange Prediction Using Sentiment Analysis of Online Textual Opinions | Bullish or Bearish instead of positive or negative |
| Not specified | 3 | 12055 | 2021 | not specified | ParsBERT Post-Training for Sentiment Analysis of Tweets Concerning Stock Market | - | |
| Multimodal-Persian-SA | 1:561, 0:439 | 1000 | Instagram, Telegram | 2021 | not specified | Sentiment Analysis of Persian Instagram Post: a Multimodal Deep Learning Approach | Multi-Modal, Text and image |
| InstaText | 3 | 8512 | 2021 | not specified | Producing An Instagram Dataset for Persian Language Sentiment Analysis Using Crowdsourcing Method | - |