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An Improved Recurrent Network for Online Equality-Constrained Quadratic Programming Read chapter Read first chapter

2016 | OriginalPaper | Chapter

PerSent: A Freely Available Persian Sentiment Lexicon

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

Published in: Advances in Brain Inspired Cognitive Systems

Publisher: Springer International Publishing

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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.

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previous chapter Incremental PCANet: A Lifelong Learning Framework to Achieve the Plasticity of both Feature and Classifier Constructions
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Metadata
Title
PerSent: A Freely Available Persian Sentiment Lexicon
Authors
Kia Dashtipour
Amir Hussain
Qiang Zhou
Alexander Gelbukh
Ahmad Y. A. Hawalah
Erik Cambria
Copyright Year
2016
Book
Advances in Brain Inspired Cognitive Systems

Print ISBN: 978-3-319-49684-9

Electronic ISBN: 978-3-319-49685-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-49685-6_28

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