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.
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EmoPars is a dataset of 30,000 Persian Tweets labeled with Ekman’s six basic emotions (Anger, Fear, Happiness, Sadness, Hatred, and Wonder). This is the first publicly available emotion dataset in the Persian language.
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ShortPersianEmo is a new data set for emotion recognition in Persian short texts. The ShortPersianEmo dataset is a single-label dataset that contains 5472 short Persian texts collected from Twitter and Digikala. Our dataset is annotated according to Rachael Jack’s emotional model in five emotional classes happiness, sadness, anger, fear, and other. Unlike publicly accessible datasets that do not impose any restrictions on text length, ShortPersianEmo specifically focuses on short texts. The average text length in the ShortPersianEmo dataset is 56 words. Table 1 presents a comparison between the introduced ShortPersianEmo dataset and other datasets from the literature for emotion detection in Persian text. For more information on this dataset please read our paper. If you use this dataset in any research work, please cite our paper.
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