01412nam a22001097a 4500100005300000245006800053260002800121300000900149520107000158650004101228856003301269  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