@article{(Open Science Index):https://publications.waset.org/pdf/10012132,
	  title     = {1/Sigma Term Weighting Scheme for Sentiment Analysis},
	  author    = {Hanan Alshaher and  Jinsheng Xu},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {15},
	  number    = {7},
	  year      = {2021},
	  pages     = {441 - 444},
	  ee        = {https://publications.waset.org/pdf/10012132},
	  url   	= {https://publications.waset.org/vol/175},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 175, 2021},
	}