Analysis of Financial News Using Natural Language Processing and Artificial Intelligence

Abstract

The task of analysis of financial news uses state of-the-art Natural Language Processing (NLP) and Artificial Intelligence (AI) techniques. The paper demonstrates how NLP techniques can be used to provide succinct summaries, identify keywords and determine sentiment of a certain news article. These features can then be used to make informed decisions that are based on recent, relevant reports. This paper also exhibits a methodology of identifying impact investment using a Naive Bayes Classifier, which can be extended to other financial terminology. We find that the usage of NLP and AI techniques such as sentiment analysis and keyword extraction enhance the information presented in online news articles by filtering out irrelevant content.