Volume 19, Issue 2 (9-2022)                   JSDP 2022, 19(2): 107-132 | Back to browse issues page


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Rajabi Z, valavi M, Hourali M. Sentiment analysis methods in Persian text: A survey. JSDP 2022; 19 (2) : 8
URL: http://jsdp.rcisp.ac.ir/article-1-1099-en.html
Iran Telecommunication Research Center (ITRC)
Abstract:   (1338 Views)
With the explosive growth of social media such as Twitter and Instagram, reviews on e-commerce websites, and comments on news websites, individuals and organizations are increasingly using analyzing opinions in these media for their decision-making and designing strategies. Sentiment analysis is one of the techniques used to analyze users' opinions in recent years. The Persian language has specific features and thereby requires unique methods and models to be adopted for sentiment analysis, which are different from those in English and other languages. This paper identifies the characteristics and limitations of the Persian language. Sentiment analysis in each language has specified prerequisites; hence, the direct use of methods, tools, and resources developed for the English language in Persian has its limitations.
The present study aims to investigate and compare previous sentiment analysis studies on Persian texts and describe views presented in articles published in the last decade. First, the sentiment analysis levels, approaches, and tasks are described. Then, a detailed survey of the applied sentiment analysis methods used for Persian texts is presented, and previous works in this field are discussed. The advantages and disadvantages of each proposed method are demonstrated. Moreover, the publicly available sentiment analysis resources of Persian texts are studied, and the characteristics and differences of each are highlighted.
As a result, according to the recent development of the sentiment analysis field, some issues and challenges not being addressed in Persian texts are listed, and some guidelines are provided for future research on Persian texts. Future requirements of Persian text for improving the sentiment analysis system are detailed.
Article number: 8
Full-Text [PDF 1363 kb]   (1354 Downloads)    
Type of Study: Research | Subject: Paper
Received: 2019/12/15 | Accepted: 2021/05/23 | Published: 2022/09/30 | ePublished: 2022/09/30

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