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

With regard to today's social media networks, memes have become centralcharacter where millions ofmemesare sharedper second on different social medianetworks. The detection of memes is a very concentrated and demanding subject in the current era. Today's social media (What's App, Twitter, and Facebook) is widespread around the world. People in all countries use these networksand spend theirplentifultimeon daily basis. As social media has an enormous amount of data overall in the world. Meme detection from media networkscan be done by using their authenticated APIs. For this analysisweusedsome opinion mining techniques and sentiment analysis like statistical descriptive and content analysis. In our society,it is the better way to analyze about any journalist because social media can provide very huge amountsof data about any journalist however the authenticity is compromised, whatis true or false, no onebother to check. Anyonecan make approximate correct perceptionsby using sentiment analysis and text mining techniques. It will provide highly wanted and hidden characteristics and perceptionsfor searchers and demanding people about journalists. Finally use for sentiment analysis by using Python.