Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

A SVM-based method for sentiment analysis in Persian language

[+] Author Affiliations
Mohammad Sadegh Hajmohammadi

Islamic Azad Univ. (Iran, Islamic Republic of)

Roliana Ibrahim

Univ. Teknologi Malaysia (Malaysia)

Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 876838 (March 20, 2013); doi:10.1117/12.2010940
Text Size: A A A
From Conference Volume 8768

  • International Conference on Graphic and Image Processing (ICGIP 2012)
  • Zeng Zhu
  • Singapore, Singapore | October 05, 2012

abstract

Persian language is the official language of Iran, Tajikistan and Afghanistan. Local online users often represent their opinions and experiences on the web with written Persian. Although the information in those reviews is valuable to potential consumers and sellers, the huge amount of web reviews make it difficult to give an unbiased evaluation to a product. In this paper, standard machine learning techniques SVM and naive Bayes are incorporated into the domain of online Persian Movie reviews to automatically classify user reviews as positive or negative and performance of these two classifiers is compared with each other in this language. The effects of feature presentations on classification performance are discussed. We find that accuracy is influenced by interaction between the classification models and the feature options. The SVM classifier achieves as well as or better accuracy than naive Bayes in Persian movie. Unigrams are proved better features than bigrams and trigrams in capturing Persian sentiment orientation. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Mohammad Sadegh Hajmohammadi and Roliana Ibrahim
" A SVM-based method for sentiment analysis in Persian language ", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 876838 (March 20, 2013); doi:10.1117/12.2010940; http://dx.doi.org/10.1117/12.2010940


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.