  Social media has been remarkably grown during the past few years. Nowadays,
posting messages on social media websites has become one of the most popular
Internet activities. The vast amount of user-generated content has made social
media the most extensive data source of public opinion. Sentiment analysis is
one of the techniques used to analyze user-generated data. 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
language. Sentiment analysis in each language has specified prerequisites;
hence, the direct use of methods, tools, and resources developed for English
language in Persian has its limitations. The main target of this paper is to
provide a comprehensive literature survey for state-of-the-art advances in
Persian sentiment analysis. In this regard, the present study aims to
investigate and compare the previous sentiment analysis studies on Persian
texts and describe contributions presented in articles published in the last
decade. First, the levels, approaches, and tasks for sentiment analysis are
described. Then, a detailed survey of the sentiment analysis methods used for
Persian texts is presented, and previous relevant works on Persian Language are
discussed. Moreover, we present in this survey the authentic and published
standard sentiment analysis resources and advances that have been done for
Persian sentiment analysis. Finally, according to the state-of-the-art
development of English sentiment analysis, some issues and challenges not being
addressed in Persian texts are listed, and some guidelines and trends are
provided for future research on Persian texts. The paper provides information
to help new or established researchers in the field as well as industry
developers who aim to deploy an operational complete sentiment analysis system.
