Correlation analysis of user influence and sentiment on Twitter data

Microbloging Twitter is a service that is widely used because of the need for rapid communication or cheaper than blogs, email, instant messaging or web. The growth of Twitter users has increased very rapidly in recent years. Thus the need for the utilization of Twitter either in the promotion of a product or the introduction of self-governance necessary for future leaders. These researches tried to calculate the popularity by calculating the value of user influence and sentiment. The research of sentiment on Indonesian text only focuses on sentiment classification. There has been no research on scoring or calculation of the sentiment value. The calculation of sentiment value is needed to determine the magnitude of a good or bad someone assessment by the value of a product or a person. Popularity analysis using Bayesian probability is to measure the value of the influence. Measurements of sentiment consist of 3 main parts such as value of verbs, adjectives, and adverbs in Indonesian language. In this research, analyze the value of influence and sentiment of someone using the Pearson correlation method. The negative correlation on President candidate is higher than positive correlation. The low sentiments value will have a greater impact to increase the influence value or vice versa. The accuracy of the sentiment on Bahasa Indonesia text is 73% It can be increased by improving the preprocessing process on Bahasa Indonesia. This research provides two contributions, namely calculating the value of sentiment on Bahasa Indonesia and analysis of sentiment and influence patterns of relationships.