• T.Sai Prasad Reddy
• CH.Bhaskar Rao
• A.Vamsi Krishna

Twitter trends, a timely updated set of top terms in Twitter, have the ability to affect the public agenda of the community and have attracted much attention. Unfortunately, in the wrong hands, Twitter trends can also be abused to mislead people. Twitter drifts, an opportune refreshed arrangement of best terms in Twitter, can influence people in general motivation of the group and have pulled in much consideration. In this project, we will verify whether Twitter patterns are secure from the control of pernicious clients. We gather more than 69 million tweets from 5 million records. Utilizing the gathered tweets, we initially lead an information investigation to know on what basis data is getting manipulated and find proof of Twitter slant control. In this project, we do research at the subject level data and induce the key factors that can decide if a theme begins slanting because of its notoriety, scope, transmission, potential scope, or notoriety.

Twitter, Slant Control, Notoriety

"A SECURE TWITTER TRENDING MANIPULATION AND TOPIC CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.1297-1300, July-2018, Available :http://www.jetir.org/papers/JETIRC006223.pdf

"A SECURE TWITTER TRENDING MANIPULATION AND TOPIC CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp1297-1300, July-2018, Available at : http://www.jetir.org/papers/JETIRC006223.pdf