2017 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation
July 5-8, 2017, Lehman Auditorium, George Washington University, Washington DC, USA
TBD
Talk title: TBA
Abstract: TBA
Huan Liu
Data Mining and Machine Learning Lab, School of Computing, Informatics, and Decision Systems Engineering - Arizona State University, Tempe, Arizona
Dr. Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He obtained his Ph.D. in Computer Science at University of Southern California. He was recognized for excellence in teaching and research in Computer Science and Engineering at Arizona State University. His research interests are in data mining, machine learning, social computing, and artificial intelligence, investigating problems that arise in real-world applications with high-dimensional data of disparate forms. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He serves on journal editorial/advisory boards and numerous conference program committees. He is a Fellow of IEEE and a member of several professional societies. For more details, visit http://www.public.asu.edu/~huanliu/.
Talk title: From AI to AI: Acquiring Social Media Intelligence via "Big" Data
Abstract: As the old adage goes, "knowledge is power". With the pervasive presence of big data, data is a new source of power. Social media data is mainly user-generated with geo-spatial, pictorial, temporal, and social information. We use social media data to acquire intelligence about user behavior, user needs, sentiment, opinions, and trends. This presentation examines issues arising from social media intelligence acquisition: why data is power, whether big data is really big, how we can solve problems or verify hypotheses with social media data, how we can obtain interpretable machine-extracted topics, and how we can figure out what we don't know. With adaptive and evolving bots, social media intelligence could be obfuscated with rampant misinformation, thus it is challenging to acquire accurate social media intelligence. With the joint force of AI and social media data, we hope to develop novel algorithms for acquiring social media intelligence with collaborative research.
Major General John Ferrari
Major General John G. Ferrari was deputy director of program analysis and evaluation within the office of the deputy chief of staff, G-8, U.S. Army, in Washington, District of Columbia. Starting in July 2014, he became director of program analysis and evaluation within the office of the deputy chief of staff, G-8, U.S. Army, in Washington, District of Columbia. Previously he served as Commanding General, White Sands Missile Range in White Sands New Mexico and Deputy Commander for Programs, Combined Security Transition Command in Afghanistan.
Talk title: Fake News and the Future of Warfare
Abstract: We are witnessing the most rapid and profound change in the global information environment in history. Furthermore, it is possibly a seminal moment in the field of military deception. The speed and reach of internet-driven information operations are not only unprecedented; the societal implications associated with them are not well understood outside the research community. In the military, our ability to adapt to this new reality is vitally important as we are in a race to understand this dynamic information ecosystem and counter capable adversaries who operate without restraint.
How vulnerable are we as a society, and how can we harness the power of social computing as it changes how we live, work, and perceive the world around us? Moreover, what are the implications of participating in this "arms race" versus simply ceding this critical terrain? The ability to defend our nation against these powerful information operations extends beyond differentiating between "real" and "fake" news, and the research community will play a vital role in informing both policy and strategy to address these challenges.