Sentiment Analysis and Stock Price Correlation: An Analytical Approach using NLP and Financial Data

Himanshu Anil Kumar Chauhan

Title:
Sentiment Analysis and Stock Price Correlation: An Analytical Approach using NLP and Financial Data

Authors:
Himanshu Anil Kumar Chauhan

Cite This Article :

Himanshu Anil Kumar Chauhan "Sentiment Analysis and Stock Price Correlation: An Analytical Approach using NLP and Financial Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025, pp.1079-1081, URL: https://www.ijtsrd.com/papers/ijtsrd79752.pdf

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Abstract :
Financial markets are increasingly influenced by investor perception and sentiment, which can be extracted and quantified using advanced Natural Language Processing (NLP) methodologies. This study explores the dynamic interplay between sentiment derived from financial news headlines and the corresponding stock prices of major Indian corporations, with a focused analysis on DLF and Adani Enterprises. Utilizing sentiment analysis models and computing Pearson correlation coefficients, the research aims to identify statistically significant relationships that may serve as early indicators for market behavior. The sentiment scores are transformed into a unified numerical representation to reflect directional and intensity-based nuances. Temporal smoothing using moving averages is also incorporated to filter market noise. The findings, supported by visual representations, suggest that sentiment analysis offers a valuable, complementary lens to traditional quantitative models in understanding stock price fluctuations.

Keywords :
Sentiment Analysis, Stock Market, Pearson Correlation, NLP, Financial News, Predictive Analytics

Publication Details:

Unique Identification Number : IJTSRD79752

Published In : Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025

Page Number(s) : 1079-1081

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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