• P.Nagarjuna

The wide spread use of Online Social Networks (OSNs) is used to disseminate information and exchange opinions. Online social media data have many applications in the intersection of political and computer science. Using online social media to predict election outcomes and personalizing social media feeds so as to provide a fair and balanced view of people’s opinions on controversial issues. The problem is to be quantifying and inferring the political leaning of twitter users. Political leaning inference as a convex problem that incorporates two ideas such as consistent users are tweeting and re-tweeting about political issues and re-tweeted by similar users. A variety of methods have been proposed to count the extent of injustice in traditional news media. This is the time taking process and some in direct methods involved linking media outlets to reference points with known political positions. The main drawback is data shortage because the amount of data available for analysis is limited and not possible to assign numerical scores for politician position. In proposed system, a convex optimization technique is used to maximize the tweet and re-tweet agreement. The data is received from the newspaper articles and quantified media. The technical contribution is to frame political leaning inference as a convex.

Twitter,Political Science,Convex Programming,Data Analytics,Inference,Signal Processing

"Broadcasting of tweets in the online social network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.536-538, July-2018, Available :http://www.jetir.org/papers/JETIR1807430.pdf

"Broadcasting of tweets in the online social network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp536-538, July-2018, Available at : http://www.jetir.org/papers/JETIR1807430.pdf