Effective Sentiment Analysis of Social Media Datasets Using Naive Bayesian Classification

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Effective sentiment analysis of social media datasets using naive Bayesian classification involves extraction of subjective information from textual data. A normal human can easily understand the sentiment of a document written in natural language based on its knowledge of understanding the polarity of words (uni-gram, bi-gram and n-grams) and in some cases the general semantics used to describe the subject. The paper aims to make the machine extract the polarity (positive, negative or neutral) of social media dataset with respect to the queried keyword.
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