Towards the Global SentiWordNet

The discipline where sentiment/opinion/emotion has been identified and classified in human written text is well known as sentiment analysis. A typical computational approach to sentiment analysis starts with prior polarity lexicons where entries are tagged with their prior out of context polarity as human beings perceive using cognitive knowledge. Till date, all research efforts found in sentiment analysis literature deal mostly with English texts. In this article, we propose an interactive gaming (Dr Sentiment) technology to create and validate SentiWordNet in 56 languages by involving Internet population. Dr Sentiment is a fictitious character, interact with players using series of questions and finally reveal the behavioral or sentimental status of any player and store the lexicons as the players polarized during playing. The interactive gaming technology is then compared with other multiple automatic linguistics techniques like, WordNet based, dictionary based, corpus based or generative approaches for generating SentiWordNet(s) for Indian languages and other International languages as well. A number of automatic, semiautomatic and manual validations and evaluation methodologies have been adopted to measure the coverage and credibility of the developed SentiWordNet(s).