In recent years social networking sites are very popular for user needs. Mostly people use an important social networking information source such as Twitter to find answers to their questions. Twitter contains microblogging services for informal information interactions. In this paper, we classify the subjective and objective questions using Naïve Bayes algorithm and also find the respondent users. For classification we build the feature extraction techniques such as lexical, syntactical and contextual in terms of the way they are asked and answered. For applying the classification on a larger dataset using other social media and analysis of performance.
Information seeking, social search, Twitter, other social networks
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