Trend-based and reputation-versed personalized news network

Abstract

Web users while collaborating over social networks and micro-blogging services also contribute to news coverage worldwide. News feeds come from mainstream media as well as from social networks. Often feeds from social networks are more up-to-date and, for user's view, more credible than those that come from mainstream media. But the overwhelming amount of information requires to personally filter through it until one gets what is really needed. In this paper, we describe our idea of a personalized news network built on current Web technologies and our research projects by filtering Twitter and Facebook messages using both trend mining and reputation approaches. Based on the example of Egyptian revolution, we explain the main idea of personalized news.