Abstract
Study of Pragmatics is a very important part of Natural Language Processing (NLP). Pragmatic analysis allows to analyze what the given text basically means. The aim is to draw inferences from the given text. This paper reports the work on pragmatics analysis performed for the Twitter data set. To understand the intended meaning behind a tweet, sentiment analysis, polarity and contextual information is used. Various machine learning algorithms including Logistic Regression, Decision Tree, Random Forests, and Support Vector Machines are used for implementation. A comparative analysis of evaluation using this algorithm is also reported.
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