Opinion Extraction of Public Figure Based on Sentiment Analysis from Twitter

Abstract

Twitter is a microblog that can generate an information from users such as sentiment about public figures. Sentiment analysis of public figure interpret the positive or negative response. This study aims to create system that automatically can extract the opinion about public figure based on sentiment analysis in twitter using two novel features, they are specific term and number of followers public figures lover and hater. Several step to determine the sentiment of public figure are preprocessing, weighting, classifying, and determining sentiment response. In this paper we use six public figures to be observed. This research resulting precision 99%, recall 75%, and accuracy 76,67%.