## 4 Datasets  
**Digikala:** ([[https://github.com/Aluniversejourney/EnhanceTextClassification/blob/main/DATASET/digikala_data.csv](https://github.com/Aluniversejourney/EnhanceTextClassification/blob/main/DATASET/digikala_data.csv)]([https://github.com/Aluniversejourney/EnhanceTextClassification/blob/main/DATASET/digikala_data.csv](https://github.com/Aluniversejourney/EnhanceTextClassification/blob/main/DATASET/digikala_data.csv)) accessed on 2 August 2023). This dataset contains user comments in Persian on various products from a store website called Digikala, which is among the largest online shops in the Persian language. The website offers a wide range (hundreds of thousands) of products, including electronic products, books, clothes, and more. Users have the opportunity to express their opinions about the products they have purchased. The dataset consists of 100,000 rows and 12 different columns, containing various forms of information such as user opinions, product advantages and disadvantages, number of likes and dislikes, product IDs, and more. The characteristics of this dataset are presented in Table 1. Each row in this dataset is related to a user's opinion about a product. Here, we removed the comments with missing labels, and in the end, about 63,000 comments remained with their labels.  
**Arabic-twitter-corpus-AJGT:** ([[https://github.com/komari6/Arabic-twitter-corpus-AJGT](https://github.com/komari6/Arabic-twitter-corpus-AJGT)]([https://github.com/komari6/Arabic-twitter-corpus-AJGT](https://github.com/komari6/Arabic-twitter-corpus-AJGT)) 2 August 2023). This dataset is an Arabic Jordanian General Tweets (AJGT) dataset, which contains 1800 tweets in Arabic, which are classified into positive and negative categories. The dataset is balanced; 900 tweets are classified in the positive class and 900 tweets are classified in the negative class.  
**DeepSentiPers:** ([[https://github.com/JoyeBright/DeepSentiPers](https://github.com/JoyeBright/DeepSentiPers)]([https://github.com/JoyeBright/DeepSentiPers](https://github.com/JoyeBright/DeepSentiPers)) 2 August 2023). This is a Persian, balanced dataset that includes users' opinions on digital products, classified into five categories. The details of this dataset are presented in Table 2.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Digikala** & **Recommended** & **No-Idea** & **Not-Recommended** & **Total** \\ \hline Label & 1 & 0 & \(-1\) & - \\ \hline Number of Data & 36,960 & 10,528 & 16,098 & **63,586** \\ \hline \hline \end{tabular}
\end{table}
Table 1: Digikala dataset.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**DeepSentiPers** & **Delighted** & **Happy** & **Natural** & **Angry** & **Furious** & **Total** \\ \hline Label & \(-2\) & \(-1\) & 0 & 1 & 2 & - \\ \hline Number of Data & 1342 & 2184 & 3152 & 697 & 40 & **7415** \\ \hline \hline \end{tabular}
\end{table}
Table 2: DeepSentiPers dataset.  
**MR:** ([[http://www.cs.cornell.edu/people/pabo/movie-review-data/](http://www.cs.cornell.edu/people/pabo/movie-review-data/)]([http://www.cs.cornell.edu/people/pabo/movie-review-data/](http://www.cs.cornell.edu/people/pabo/movie-review-data/)) 2 August 2023). This dataset is used for binary sentiment analysis, which includes user comments in English about different movies. These comments are classified into two categories: positive and negative; 5331 data are found in the positive class and 5331 data are found in the negative class.