%0 Journal Article
	%A Hanan Alshaher and  Jinsheng Xu
	%D 2021
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 175, 2021
	%T 1/Sigma Term Weighting Scheme for Sentiment Analysis
	%U https://publications.waset.org/pdf/10012132
	%V 175
	%X Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.
	%P 441 - 444