SENTIMENT ANALYSIS OF DATA MINING TECHNIQUES FOR SOCIAL NETWORKS

Abstract

Sentiment analysis is defined as the task of finding and analyzing the opinions of authors about specific entities or topic. Social network has increased astounding consideration in the most recent decade. Getting to Social network destinations, for example, Twitter, Facebook LinkedIn and Google+ through the web and the web 2.0 innovations has turned out to be more moderate. Data mining gives an extensive variety of methods for identifying helpful learning from enormous datasets like pat- terns, examples and tenets. Data mining methods are utilized for data recovery, measurable displaying and machine learning. These strategies utilize data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey talks about various in Data mining methods used as a piece of mining differing parts of the Social network over decades going from the verifiable procedures to the up to date models. Twitter is a miniaturized scale blogging administration worked to find what is going on at any minute in time, anyplace on the planet. Twitter messages are short, and created always, and appropriate for learning revelation utilizing information stream mining.