Navigating Challenges and Future Trends in Sentiment Analysis for Investment Decision Making

Abstract

Sentiment analysis is a computerised approach for evaluating and interpreting the emotions, attitudes, and views represented in text. It is a robust natural language processing approach that has attracted of a lot of interest in investment decision making. Sentiment analysis provides insights that guide investment decisions by analysing and interpreting sentiment from textual data sources such as news articles, social media posts, and financial reports. However, using sentiment analysis to make financial decisions has its own set of issues and constraints. This study investigates the challenges of sentiment analysis as well as future trends and prospects.