Analysis of News Sentiment and Stock Price Using Web Scraping and Vader Sentiment Analysis

Rapid development of the information technologies and methods has contributed to the advancement of financial stock analysis and prediction. This paper focuses on investigating Bank Mandiri stock sentiments from financial news data using web scraping and VADER sentiment analysis to obtain accurate news polarity scores. The dynamical alignment and changes between the resulting sentiment analysis and stock prices towards neutral, bullish and bearish stock movements can subsequently be identified and evaluated using Pearson's and Spearman's correlation coefficients for the model refinement. The research results over market conditions indicate that there are consistent alignment and direction between stock sentiments from the financial news and dynamical stock price changes. This work can provide some benefits and insight for the financial investors and stock traders in making a better decision.