Meme Detection of Journalists from Social Media by Using Data Mining Techniques

Abstract

With regard to today's social media networks, memes have become central. Share a million memes per second on different social media. The detection of memes is a very concentrated and demanding subject in the current field of research. Share about a million memes on various social media. Today's social media (What's App, Twitter, and Facebook) is widespread around the world. Since people in all countries are heavily used, use a set of social media application data (Twitter). As social media has an enormous amount of data overall the world. That will use that data set of Twitter for meme detection of journalists in Pakistan. So, this is done by getting data set from social media (Twitter, What’s App, and Facebook) by using their authenticated APIs. For this analysis use some opinion mining techniques and sentiment analysis like the statistical descriptive and content analysis. In our society, it is the better way to analysis about any journalists because social media can provide very huge amounts of data about any journalist which is true or false but I can make approximate correct perceptions by using sentiment analysis and text mining techniques. It will provide highly wanted and hidden characteristics and perceptions for searchers and demanding people about journalists. Finally use for sentiment analysis by using Python.