PerSent: A freely available Persian sentiment lexicon

Dashtipour, Kia; Hussain, Amir; Zhou, Qiang; Gelbukh, Alexander; Hawalah, Ahmad Y. A.; Cambria, Erik

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.

Citation

Dashtipour, K., Hussain, A., Zhou, Q., Gelbukh, A., Hawalah, A. Y. A., & Cambria, E. (2016, November). PerSent: A freely available Persian sentiment lexicon. Presented at BICS 2016: International Conference on Brain Inspired Cognitive Systems, Beijing, China

• Presentation Conference Type: Conference Paper (published)
• Conference Name: BICS 2016: International Conference on Brain Inspired Cognitive Systems
• Start Date: Nov 28, 2016
• End Date: Nov 30, 2016
• Online Publication Date: Nov 13, 2016
• Publication Date: 2016
• Deposit Date: Oct 4, 2019
• Publisher: Springer
• Pages: 310-320
• Series Title: Lecture Notes in Computer Science
• Series Number: 10023
• Series ISSN: 0302-9743
• Book Title: Advances in Brain Inspired Cognitive Systems
• ISBN: 978-3-319-49684-9
• DOI: https://doi.org/10.1007/978-3-319-49685-6_28
• Keywords: sentiment analysis; Persian; machine-learning; sentiment lexicon
• Public URL: http://researchrepository.napier.ac.uk/Output/1792751