Sentiment Analysis for Financial Market Predictions: Leveraging Deep Learning for Data-Driven Insights

EasyChair Preprint 15384

Abstract

Sentiment analysis, powered by deep learning, has proven effective in capturing market sentiments and providing predictive insights for financial markets. By analyzing news articles, social media, and financial reports, sentiment analysis models help anticipate stock price movements, investor behavior, and market trends. This paper explores the application of deep learning techniques, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), in sentiment analysis to forecast financial market changes. A case study of recent market trends showcases the effectiveness of sentiment-driven predictions, offering a robust approach to data-driven financial forecasting.

Keyphrases: Convolutional Neural Networks, Data-driven insights, Financial market prediction, Recurrent Neural Networks, Sentiment Analysis, deep learning, investor sentiment

@booklet{EasyChair:15384,
  author    = {Isabella Rossi},
  title     = {Sentiment Analysis for Financial Market Predictions: Leveraging Deep Learning for Data-Driven Insights},
  howpublished = {EasyChair Preprint 15384},
  year      = {EasyChair, 2024}}