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ARTFSC – Average Relative Term Frequency Sentiment Classification
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY
Sentiment Classification refers to the computational techniques for classifying whether the sentiments of text are positive or negative. Statistical Techniques based on Term Presence and Term Frequency, using Support Vector Machine are popularly used for Sentiment Classification. This paper presents an approach for classifying a term as positive or negative based on its average frequency in positively tagged documents in comparison with negatively tagged documents. Our approach is based on termdoi:10.24297/ijct.v12i6.3141 fatcat:ucrpybjuizf2pgsytnnmxk53qu