Stock Market Prediction Using Sentiment Analysis

Abstract

Social sites like Twitter help millions of people to share their thoughts about the Stock market and what they feel about them. The tweet may be a short and easy sort of expression. Detecting sentiments in-text features a wide selection of applications including identifying anxiety or depression of people and measuring the well-being or mood of a community. Therefore, during this review paper, we focused on Sentiment Analysis of Twitter data. Sentiments are often expressed in some ways, which will be seen like countenance and gestures, speech, and transcription. Sentiment Analysis in text documents is actually a content-based classification problem involving concepts from the domains of tongue processing also as Machine Learning. Using different aspects, the research of Sentiment Analysis of Twitter Data is often performed. We can see the various sorts of Sentiment Analysis and techniques want to perform the extraction of the info. In this paper, we have taken a comparative study of various approaches and techniques of sentiment analysis having Twitter as knowledge.