01579nam a22001457a 4500999001700000100005300017245006800070260002800138300000900166520107000175650004101245856003301286942001101319952010301330  c68385d68382  aAakash Ali Sahito a17-MSIT-01aDr.Adnan Manzoor  aSarcasm Detection of Political News on Social Media (MS THESIS)  aQUEST bNawabshahc2023  a51p.  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  aDepartment of Information Technology  uhttps://tinyurl.com/ynbd77tx  cTHESIS  00104070aRESEARCHbRESEARCHd2024-07-26l0pMP/90-1310r2024-07-26 00:00:00w2024-07-26yTHESIS