Detecting Emotional Impact on Young Minds Based on Web Page Text Classification Using Data Analytics and Machine Learning

This paper evaluates the text classification method of determining emotions. In this study, we determined the emotion that a random set of web pages depicts. The emotions stated by young people was compared with the emotions determined by the machine. The emotions from web pages were determined by calculating the score of basic emotions based on emotion lexicon [1, 2] ANOVA test shows significant difference for at least two of the emotions. Practical significance of this approach is to determine the emotional impact on college goers aged between 17–20 while reading webpages. Experiments in this paper concluded that the texts from the web pages affects the college goers emotionally. We determined the emotional impact on that particular age group simply by classifying text and calculating emotion score. Machines perfectly determined human emotions by classifying webpages which almost matched with the emotions stated by college-goers with a couple of exceptions.