رحیم دهخوارقانی

There is no doubt about the usefulness of public opinion toward different issues in social media and the World Wide Web. Extracting the feelings of people about an issue from text is not straightforward. Polarity lexicons that assign polarity tags or scores to words and phrases play an important role in sentiment analysis systems. As English is the richest language in this area, getting benefits from existing English resources in order to build new ones has attracted the interest of many researchers in recent years. In this article, we propose a new translation-based approach for building polarity resources in resource-lean languages such as Persian. The results of empirical evaluation of the proposed approach prove its effectiveness. The generated resource is the largest publicly available polarity lexicon for Persian.