Abstract
People need to know other people’s opinions to make well-informed decisions to buy products or services. Companies and organizations need to understand people’s attitude towards their products and services and use feedback from the customers to improve their products. Sentiment analysis techniques address these needs. While the majority of Internet users are not English speakers, most research papers in the sentiment-analysis field focus on English; resources for other languages are scarce. In this paper, we introduce a Persian sentiment lexicon, which consists of 1500 words along with their part-of-speech tags and polarity scores. We have used two machine-learning algorithms to evaluate the performance of this resource on a sentiment analysis task. The lexicon is freely available and can be downloaded from our website.
Cite
CITATION STYLE
Dashtipour, K., Hussain, A., Zhou, Q., Gelbukh, A., Hawalah, A. Y. A., & Cambria, E. (2016). PerSent: A freely available persian sentiment lexicon. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10023 LNAI, pp. 310–320). Springer Verlag. https://doi.org/10.1007/978-3-319-49685-6_28
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