Implementation On Sarcasm Detection On Twitter Data


One of the hot topics of recent years is analyzing or extracting microblog data. Analysis of feelings is one of the micro-blog data analysis techniques. Analysis of feelings refers to Identification of online courage and opinion with regard to an explicit theme or product. Sarcasm is one of the most frequently used ironies in micro-blogs or social network sites. Sarcasm is another way of transmitting information from person to person. It could be used in different ways, such as mockery of somebody. One of the key principles for enhancing data analysis and developing automatic feeling analytics is sarcasm detection. In this paper we propose an approach based on a pattern for tweet iron detection. We proposed to use a pattern-based approach to make a feeling study. We also research the significance and the price for the grouping of each proposed feature set. Keywords: Twitter, Sarcasm Detection, Sentiment Analysis, Pattern Based Approach, Machine Learning.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL