A rapid increase in social networking services in recent years has enabled people to share and seek information effectively. Meanwhile, the openness and timeliness of social networking sites also allow for the rapid creating and dissemination of misinformation. As witnessed in recent incidents of fake news, misinformation escalates quickly and can impact social media users with undesirable consequences and wreak havoc instantaneously. Despite many people have been aware of that fake news and rumors are misleading the public and even compromising elections, the problem is not going away. In this tutorial, we will discuss how misinformation gains traction in the race for attention, introduce emerging challenges of identifying misinformation, present a comparative survey of current data mining research in tackling the challenges, and suggest available resources and point to directions for future work.
This tutorial will target researchers and practitioners who are interested in the area of misinformation mining and have basic knowledge of network analysis, data mining, and machine learning. It will be delivered at a college junior/senior level, and should be easily accessible to interested parties from both industry and academia.
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-  Xiaoyan Qiu, Diego FM Oliveira, Alireza Sahami Shirazi, Alessandro Flammini, and Filippo Menczer. Limited individual attention and online virality of low-quality information. Nature Human Behavior 1 (2017): 0132. pdf