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PerSent: A freely available Persian sentiment lexicon

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

Authors

Kia Dashtipour

Qiang Zhou

Alexander Gelbukh

Ahmad Y. A. Hawalah

Erik Cambria



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.

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