Novel Approach For Sentiment Analysis Over Social Networks

Abstract

Sentiment analysis is the computational study of opinions, appraisals, attitudes and newlineemotions towards the entities and their attributes. A basic task of sentiment analysis is newlineto identify the sentiment polarity of the documents, sentences or aspects. Human newlineaffective states are considered to determine sentiment expressed. Generally, users newlineexpress their opinion about the products, movies, shopping sites or review sites. newlineSuch kind of opinion related contents are overwhelming and growing exponentially newlinewhich becomes a tedious work for the manufacturer to classify these contents newlinemanually. Moreover, people are expecting the opinion about the entities in aspects newlinelevel. Hence, it is necessary to construct an automatic sentiment analyser which newlineautomatically identifies the sentiment polarity of the documents/aspects in bipolarity newlinelevel and multi polarity level. With the development of the social networking newlineapplications, people are able to publicly express their opinion through social media. newlineThis provides a rich source of feedback and analysis of emotions and stimulates the newlinedevelopment of automatic sentimental analysis. In recent years, classification and newlineanalysis of user reviews or opinions are becoming one of the significant aspect of newlinesentiment analysis. It involves finding the polarity of each review created by the user newlineon social networking through opinion mining. The three review polarity indicators are newlinenumbers, ratings and words for classification. Therefore, various machine learning newlinetechniques have been applied to analyze the sentiments of the but these newlinetechniques fail to achieve desired performance parameters like classification newlineaccuracy, precision, recall and F-measure because of existing classification problems