Sentiment Analysis of Persian Language: Review of Algorithms, Approaches and Datasets
Sentiment analysis aims to extract people's emotions and opinion from their
comments on the web. It widely used in businesses to detect sentiment in social
data, gauge brand reputation, and understand customers. Most of articles in
this area have concentrated on the English language whereas there are limited
resources for Persian language. In this review paper, recent published articles
between 2018 and 2022 in sentiment analysis in Persian Language have been
collected and their methods, approach and dataset will be explained and
analyzed. Almost all the methods used to solve sentiment analysis are machine
learning and deep learning. The purpose of this paper is to examine 40
different approach sentiment analysis in the Persian Language, analysis
datasets along with the accuracy of the algorithms applied to them and also
review strengths and weaknesses of each. Among all the methods, transformers
such as BERT and RNN Neural Networks such as LSTM and Bi-LSTM have achieved
higher accuracy in the sentiment analysis. In addition to the methods and
approaches, the datasets reviewed are listed between 2018 and 2022 and
information about each dataset and its details are provided.