V3I6P11

SENTIMENT ANALYSIS IN STOCK MARKET

Pavan Gogate T S^1*, Abhiram B V², Rajat R³, Akash M⁴

Abstract

The stock market is influenced by numerous factors, including economic conditions, corporate performance, and external events. However, investor sentiment plays a crucial yet often underestimated role in market dynamics. Investor sentiment, shaped bMy psychological influences, news, and social media discussions, significantly impacts stock price fluctuations and market volatility. Recent advancements in sentiment analysis leverage machine learning, text mining, and social media data to quantify sentiment and predict market movements more accurately.

This paper explores the relationship between investor sentiment and stock market volatility, emphasizing how sentiment-driven trading behaviours influence market trends. A systematic literature review highlights key findings from previous research, including the effects of short selling on volatility, the role of social media sentiment in predicting stock returns, and the implications of information asymmetry on market fluctuations. Despite these insights, challenges persist in achieving real-time accuracy, integrating diverse data sources, and addressing linguistic ambiguities in sentiment analysis.

The study identifies research gaps, including the need for multimodal sentiment analysis incorporating text, audio, and image-based data, the lack of high-quality labelled datasets, and the necessity for explainable AI models to enhance transparency. Future research directions should focus on improving dataset quality, developing AI-driven explainability techniques, and expanding sentiment analysis across multiple markets for better generalizability.

Findings suggest that while sentiment analysis is effective in short-term stock predictions, challenges such as misinformation, sarcasm, and financial jargon reduce its precision. This study contributes to the ongoing development of sentiment analysis in financial markets by identifying key trends, challenges, and opportunities for future research.

Keywords:

Volatility, Investor Sentiment, Social media Sentiment, Forecasting, Stock market, variations.