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

Sajawal Khan; Adeel Ashraf; Muhammad Shoaib; Muhammad Iftikhar; Imran Siddiq; Muhammad Dawood Khan; Abdullah Faisal

Authors

Sajawal Khan Department of Computer Science, Afro Asian Institute, Lahore, Pakistan
Adeel Ashraf Department of Information Technology, Afro Asian Institute, Lahore, Pakistan
Muhammad Shoaib Aspire College, Manawan Campus, Lahore, Pakistan
Muhammad Iftikhar PHP Laravel developer
Imran Siddiq Department of Information Technology, Afro Asian Institute, Lahore, Pakistan
Muhammad Dawood Khan Computer Science at Layyah Campus GCUF, Pakistan
Abdullah Faisal Department of Information Technology, Afro Asian Institute, Lahore, Pakistan

Keywords:

Meme Detection, Journalists, Social Media, Data Mining, Python, Sentiment Analysis

Abstract

With regard to today's social media networks, memes have become central character where millions of memes are shared per second on different social media networks. 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 networks and spend their plentiful time on daily basis. As social media has an enormous amount of data overall in the world. Meme detection from media networks can be done by using their authenticated APIs. For this analysis we used some 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 amounts of data about any journalist however the authenticity is compromised, what is true or false, no one bother to check. Anyone 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.

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