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Talk Title: Adversarial Collusion on the Web: State-of-the-art and Future Directions

Talk Abstract: The growth and popularity of online media have made it the most important platform for collaboration and communication among its users. Given its tremendous growth, the social reputation of an entity in online media plays an important role. This has led to users choosing artificial ways to gain social reputation by means of blackmarket services as the natural way to boost social reputation is time-consuming. We refer to such artificial ways of boosting social reputation as collusion. In this talk, we will comprehensively review recent developments in analyzing and detecting collusive entities on online media. First, we give an overview of the problem and motivate the need to detect these entities. Second, we survey the state-of-the-art models that range from designing feature-based methods to more complex models, such as using deep learning architectures and advanced graph concepts. Third, we detail the annotation guidelines, provide a description of tools/applications and explain the publicly available datasets. The talk concludes with a discussion of future trends.

Bio: Hridoy Sankar Dutta is currently pursuing his Ph.D. in Computer Science and Engineering from IIIT-Delhi, India. Starting January 2021, he will be joining University of Cambridge as a Research Assistant in the Cambridge Cybercrime Centre. His current research interests include data-driven cybersecurity, social network analysis, natural language processing, and applied machine learning. He received his B.Tech degree in Computer Science and Engineering from Institute of Science and Technology, Gauhati University, India in 2013. From 2014 to 2015, he worked as an Assistant Project Engineer at the Indian Institute of Technology, Guwahati (IIT-G), India, for the project ‘Development of Text to Speech System in Assamese and Manipuri Languages’. He completed his M.Tech in Computer Science and Engineering from NIT Durgapur, India in 2015. More details can be found at