Track: Data Analytics and Big Data
This study aims to obtain the results of how much value is formed from the relationship between issues and stock prices, and how the dynamics that occur between issues on stock prices and any increase or decrease in stock prices are related to repetitive issues.
The technique used in this research is using Social Network analysis, Investment, Market Effiesient, Market Analysis, Sentiment Analysis sentiment analysis, the data used is based on User Generated Content (UGC), where the data is taken from social media which contains content created in looking for issues related to stock prices, and the movement of rising and falling stock prices taken from the IDX.
The result of this research are stock issues are influenced by positive sentiment from the market with a positive response of 81% and a negative 19%. In addition, 63% are influenced by micro (small) scale external issues. The classification results generated using the Suppori Vector Machine (SVM) model are more suitable than the Naïve Bayes Classifier (NBC)
Keywords: Social Network analysis; Invesment, Market Effiesient; Market Analysist; Sentiment Analysis