000			01470nam a22001337a 4500
999			_c68385 _d68382
100			_aAakash Ali Sahito _a17-MSIT-01 _aDr.Adnan Manzoor
245			_aSarcasm Detection of Political News on Social Media (MS THESIS)
260			_aQUEST _bNawabshah _c2023
300			_a51p.
520			_aABSTRACT Sarcasm is an omnipresent fact of language in documents that are prosent on internet that express negative remarks in positive way. Finding sarcasm is of hugs significanes and helpful to many applications of Natural Language Processing, such as analysis of sentiment, opinion mining and product reviews. On-going studies consider detection of automatic sarcasm as a simple text classification issue. The study does not use explicit features for detection of sarcasm and ignore the difference between sarcastic and nom sarcastic samples in real applications. In this thesis, we first explore the individuality of existing approaches to detect sarcasm in written text. Then, we propose an approach with best rate of classification and less rate of misclassification of sarcasm. We evaluate different methods like SVM, LDA, KNN & RF and get an outcome of better method in this regard with less ratio of false-positives outputs. Keywords: Sentiment Analysis; Opinion Mining, Reviews; Text Analysis; Bag-Of- Words; Sentiment Analysis Challenges: Accuracy. xi
650			_aDepartment of Information Technology
856			_uhttps://tinyurl.com/ynbd77tx
942			_cTHESIS