SARCASM DETECTION AND SURVEYING USER AFFECTATION
Journal Title: World Journal of Engineering Research and Technology - Year 2018, Vol 4, Issue 4
Abstract
Sentiment Analysis is a technique to identify people‟s opinion, attitude, sentiment, and emotion towards any specific target such as individuals, events, topics, product, organizations, services etc. Sarcasm is a special kind of sentiment that comprise of words which mean the opposite of what you really want to say. Sarcasm is a sort of sentiment where public expresses their negative emotions using positive word within the text. It is very hard for humans to acknowledge. In this way we show the interest in sarcasm detection of social media text, particularly in tweets. In this paper we study new method pattern based approach for sarcasm detection, and also used behavioral modeling approach for effective sarcasm detection by analyzing the content of tweets however by conjoint exploiting the activity traits of users derived from their past activities. By using the various classifiers such as Random Forest, Support Vector Machine (SVM), k Nearest Neighbors (k- NN) and Maximum Entropy, we check the accuracy and performance.
Authors and Affiliations
S. Maheswari
Keywords
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- EP ID EP662381
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