Identifying top-k consistent news-casters on twitter

Abstract

News-casters are Twitter users who periodically pick up interesting news from online news media and spread it to their followers' network. Existing works on Twitter user analysis have only analysed a pre-defined set of users for user modeling, influence analysis and news recommendation. The problem of identifying prominent, trustworthy and consistent news-casters is unaddressed so far. In this paper, we present a framework, NCFinder, to discover top-k consistent news-casters directly from Twitter. NCFinder uses news headlines published in online news sources to periodically collect authentic news-tweets and processes them to discover news-casters, news sources and news concepts. Next, NCFinder builds a tripartite graph among news-casters, news source and news concepts and employs HITS algorithm on it to score the news-casters on daily basis. The daily score profiles of the news-casters collected over a time-period are then used to infer top-k consistent news-casters. We run NCFinder from 11th Nov. to 24th Nov., 2014 and discover top-100 consistent news-casters and their profile information.