• Pritesh Mahadev Patil
• Lavesh Eknath Desai
• Viraj Ashok Mhatre
• Jitesh Vishwajit Mali
• Dr. Sharvari S. Govilkar

In today’s fast-paced financial markets, news plays a major role in shaping stock prices and influencing investment decisions. From financial publications to social media, the constant influx of information can be overwhelming, making it difficult for investors to extract actionable insights. This research introduces a novel framework that integrates news sentiment analysis with stock market prediction, leveraging advanced natural language processing (NLP) and machine learning (ML) techniques to uncover sentiment patterns that may indicate market trends. The study examines the influence of both general financial news and company-specific news on stock prices, providing a comprehensive view of how sentiment impacts market behavior. Additionally, the framework explores the timing, frequency, and context of news events to enhance predictive accuracy. By systematically analyzing news sentiment alongside historical stock data, this research equips investors with deeper insights into market dynamics, improving decision-making and risk assessment. The proposed framework has the potential to transform traditional stock analysis by incorporating real-time sentiment-driven insights, offering a data-driven approach to navigating financial markets with greater confidence and precision.

Sentiment analysis, Natural language processing (NLP), Machine learning (ML), Text classification

"News Based Analysis For Stock Market Trends", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.i424-i432, April-2025, Available :http://www.jetir.org/papers/JETIR2504857.pdf

"News Based Analysis For Stock Market Trends", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppi424-i432, April-2025, Available at : http://www.jetir.org/papers/JETIR2504857.pdf