Hridesh Gupta, Pankaj Sharma
Microblogging is a very common mode of communication among internet users. Microblogs are real time content published by people and this content is generally laden with personal opinions about a variety of aspects in everyday life. This makes microblogs a rich source of data for opinion mining. We use a corpus from the popular microblogging website, Twitter [1]. We consider microblogs from the period before the Prime minister’s elections in India in 2014 to analyze the collective sentiment of the microbloggers, against and in favor of each Prime Minister candidate. We classify the microblogs to positive and negative opinion classes and we use machine learning classification techniques achieve this and translator translate the all language reviews and microblogs convert to Hindi language.
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