Deep Learning-Based Financial Sentiment Analysis (DLBFSA) is a deep learning algorithm that analyzes financial news and social media to gauge market sentiment and make informed trading decisions.

Have you ever wondered how businesses sift through mountains of customer feedback to uncover what truly matters? Imagine receiving hundreds, if not thousands, of ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...

Understanding what the markets will do before the competition realizes the same thing is a cornerstone of success in the financial services industry. While talented market watchers rely on their own ...

1 Department of Health Data Science and Biostatistics, University of Texas Southwestern Medical Center, Dallas, TX, United States 2 Department of Bioinformatics, University of Texas Southwestern ...

The analysis pipeline was implemented using Python’s Natural Language Toolkit, Gensim, and scikit-learn libraries, with hyperparameter tuning to maximize model performance. Results: Sentiment analysis ...

Abstract: This study investigates sentiment analysis method-ologies using two distinct datasets: the IMDb Movie Reviews corpus and a novel Financial Sentiment dataset. Employing a comprehensive ...

Accurate prediction of stock prices remains a fundamental challenge in financial markets, with substantial implications for investment strategies and decision making. Although machine learning and ...