Political Leaning system from social media

Ayesha Siddiqui, V. Krishna Reddy


The across the board utilization of online interpersonal organizations (OSNs) to disperse data and trade suppositions, by the overall population, news media and political on-screen characters alike, has empowered new roads of research in computational political science. In this paper, we contemplate the issue of evaluating and surmising the political inclining of Twitter clients. We define political inclining surmising as an arched advancement issue that joins two thoughts: (a) clients are reliable in their activities of tweeting and retweeting about political issues, and (b) comparable clients have a tendency to be retweeted by comparable group of onlookers. We at that point apply our derivation system to 119 million decision related tweets gathered in seven months amid the 2012 U.S. presidential race battle. On an arrangement of much of the time retweeted sources, our system accomplishes 94% exactness and high rank connection as contrasted and physically made marks. By concentrate the political inclining of 1,000 regularly retweeted sources, 232,000 customary clients who retweeted them, and the hashtags utilized by these sources, our quantitative examination reveals insight into the political socioeconomics of the Twitter populace, and the transient elements of political polarization as occasions unfurl.

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