DescriptionSocial networks have already emerged as a significant medium for the widespread distribution of news and instructions in mass convergence events such as the 2008 U.S. Presidential Election, the 2009 Presidential election in Iran, and emergencies like the landfall of Hurricanes Ike and Gustav in the fall of 2008. Use of social networks such as Facebook and Twitter has also been noted as providing great ease during the recent demonstrations in Middle East. In light of these notable outcomes, understanding information diffusion over online social networks is a critical research goal. This greater understanding can be achieved through data analysis, the development of reliable models that can predict outcomes of social processes, and ultimately the creation of applications that can shape the outcome of these processes. In this tutorial, we aim to provide an overview of such recent research based on a wide variety of techniques such as optimization algorithms, data mining, data streams covering a large number of problems such as influence spread maximization, misinformation limitation and study of trends in online social networks.
No resources found.
No links found.