![]() ![]() Only emerge and thus become visible when dealing with lots of data. Propagation of information on the blogosphere, and propose algorithms to efficiently findĪ central topic of our thesis is also the analysis of large datasets as certain network properties Person product recommendation network and its effect on purchases. Our recent work included the study of the spread of influence in a large personto. The patterns of influence that these blocks have on information or virus propagation over the ![]() We aim to identify building blocks of the networks and find It can help us spot anomalous graphs and outliers, forecast future graph structure and runĪnother important aspect of our research is the study of “local” patterns and structures In addition, our work has a wide range of applications: We then develop models that explain processes which govern the network evolution,įit such models to real networks, and use them to generate realistic graphs or give formalĮxplanations about their properties. Time evolving networks, which change some of the basic assumptions that were made in the In our work we found very interesting and counterintuitive patterns for A basic premise behind the study of large networks is that interaction leads to complexĬollective behavior. ![]()
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