Abstract

This article reports on an Emotion Analyser, a new application based on our text-to-emotion engine, which identifies emotion contained in news articles. In addition the link between the detected emotion and the future movements of the Stock Market value are investigated. The text-to-emotion engine can automatically analyse sentences input by the user and identifies the emotional content. The Emotion Analyser has been adapted to analyse Stock Market newspaper articles by searching for words that indicate the "mood" of the market. An experiment that compared the emotions identified in articles about the Stock Market to the next day’s Stock Market prices is described. The conditions in which a significant correlation can be found between the movement of the "mood" of the market and the movement of the next day's Stock Market index value are identified.