The Automatic Identification of the Emotion Status of Web Pages

A system has been developed that analyses the emotional content of web pages. Text is extracted from an embedded Internet browser and sent to a text-to-emotion engine that identifies the emotive content. An experiment was conducted that examines the effect the emotional content of the web page has on the reader. Our Online Emotion Stock Analyser application was used to assess the emotional content of web pages displaying articles that comment on the previous day's Stock Market share prices. The relevant emotive words relate to the up and down movement of share prices. The relative movement of the positive and negative emotions expressed in the articles over time was compared with the relative movement of the value of the London Stock Exchange. The experiment results support the loop effect between published articles and the future movement of share prices. A number of significant relationships have been observed between the emotion contained in articles about the Stock Market and the next day's market value. The output of the Online Emotion Analyser was shown to be a more accurate predictor of the next day’s movement of the Stock Market share index than viewing the previous movement of the index.