Social media mining for sensing and responding to real-world trends and events
By Yiannis Kompatsiaris
Social media have transformed the Web into an interactive sharing platform where users upload data and media, comment on, and share this content within their social circles. The large-scale availability of user-generated content in social media platforms has opened up new possibilities for studying and understanding real-world phenomena, trends and events. The objective of this talk is to provide an overview of social media mining, which offers a unique opportunity to to discover, collect, and extract relevant information in order to provide useful insights. It will include key challenges and issues, such as fighting misinformation, data collection, analysis and visualization components, applications, results and demos from multiple areas ranging from news to environmental and security ones.
Dr. Ioannis (Yiannis) Kompatsiaris is a Researcher Director at CERTH-ITI, the Head of Multimedia Knowledge and Social Media Analytics Laboratory and Deputy Director of the Institute.
His research interests include multimedia, big data and social media analytics, semantics, human computer interfaces (AR and BCI), eHealth, security and culture applications. He is the co-author of 129 papers in refereed journals, 46 book chapters, 8 patents and more than 420 papers in international conferences. Since 2001, Dr. Kompatsiaris has participated in 59 National and European research programs including direct collaboration with industry, in 15 of which he has been the Project Coordinator and in 41 the Principal Investigator.
He is co-editor of the books “Semantic Multimedia and Ontologies: Theory and Applications” and “TV Content Analysis: Techniques and Applications”, the guest editor of eight special issues, including “Social Media as Sensors” in IEEE Transactions on Multimedia and he has served as a program committee member and regular reviewer for a number of international journals and conferences. He has been the co-organizer of various conferences and workshops, such as the MMM 2019, ΙΕΕΕ IVMSP 2018, ACM CIVR 2009, WIAMIS 2007 and SSMS 2012 and he was a program co-chair for ACM MM 2016.
He is a Senior Member of IEEE and member of ACM.
Talk Title Will Be Uploaded Soon...
By Balaram Ravindran
Abstract will be uploaded soon...
Prof. Balaram Ravindran is an associate professor at the Department of Computer Science and Engineering at the Indian Institute of Technology Madras. He completed his Ph.D. at the Department of Computer Science, University of Massachusetts, Amherst. He worked with Prof. Andrew G. Barto on an algebraic framework for abstraction in Reinforcement Learning.
His current research interests span the broader area of machine learning, ranging from Spatio-temporal Abstractions in Reinforcement Learning to social network analysis and Data/Text Mining. Much of the work in his group is directed toward understanding interactions and learning from them.