In the era of social networking, immense amount of posts, comments and tweets generated every second are increasing the size of social database. The analysis of this voluminous data is necessary for exploring the orientation of people's opinion about a particular entity. Most of the online data are in English language, but due to increase in technology and improved awareness of people, the online data available in Indian languages are gradually increasing. Sentiment analysis of English language alone is not sufficient to know the inclination of people towards an entity, other Indian language sentiment analysis is a must, their contribution is also important for us. The available sentiment classification lexicon resources like Hindi SentiWordNet are generic in nature and hence results in average sentiment classification accuracy due to contextual dependency. To improve the sentiment classification accuracy, we present an improvised lexicon resource for Hindi language for Hotel and Movie domains. The improvised polarity lexicon has been built reflecting context sensitivity and to increase coverage it has been expanded used synonyms based approach. The built polarity lexicon resource showcases an improvement in accuracy of 42% and 78% in Movie and Hotel domain, respectively, compared to the existing Hindi SentiWordNet lexicon resource.
cited By 0; Conference of 6th International Conference On Advances In Computing and Communications, ICACC 2016 ; Conference Date: 6 September 2016 Through 8 September 2016; Conference Code:131418
D. Mishra, Manju Venugopalan, and Dr. Deepa Gupta, “Context Specific Lexicon for Hindi Reviews”, in Procedia Computer Science, 2016, vol. 93, pp. 554 - 563.