SCAN: Socio-Cultural Attitudinal Networks

MURI Review Session, August 2020

Time (EST) Speaker Title
12:00 - 13:15 V.S. Subrahmanian
Dartmouth College		 Main Contributions of the SCAN MURI
Slides
13:15 - 13:25 Break
13:25 - 13:50 Norah Dunbar
University of California Santa Barbara		 Deception Detection: Social Science Research
Slides
13:50 - 14:15 Dimitris Metaxas
Rutgers University		 Deception Detection: Predictive Computational Modeling
Slides
14:15 - 14:25 Break
14:25 - 14:50 Judee Burgoon
University of Arizona		 Dominance Analysis: Social Science Research
Slides
14:50 - 15:15 Jure Leskovec
Stanford University		 Dominance Analysis: Predictive Computational Modeling
Slides
15:15 - 15:25 Break
15:25 - 15:50 Miriam Metzger
University of California Santa Barbara		 Cultural Analysis
Slides
15:50 - 16:00 Jay Nunamaker
University of Arizona		 New Results: Trust Prediction
Slides
Automatic Long-Term Deception Detection in Group Interaction Videos
Maksim Bolonkin, Dartmouth College


Predicting Negative Impressions in Group Interaction Videos
Maksim Bolonkin, Dartmouth College


Predicting Dominance in Group Interaction Videos
Chongyang Bai, Dartmouth College


Predicting the Visual Focus of Attention in Multi-Person Discussion Videos
Chongyang Bai, Dartmouth College


M2P2: Multimodal Persuasion Prediction with Adaptive Fusion
Chongyang Bai, Dartmouth College


Predicting Relative Nervousness from Group Interaction Videos
Viney Regunath, Dartmouth College


Deception Detection in Videos using Robust Facial Features
Anastasios Stathopoulos, Rutgers University


Dynamic Network Representation Learning
Pan Li, Stanford University


F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams
Yen-Yu Chang, Stanford University


TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Network
Yanbang Wang, Stanford University


Transcript Maagement
Mohemmad Hansia, UCSB


Measuring Similarity -- Anna Karenina (Annak)
Yibei Chen, UCSB


Transcribing Speech in the SCAN Project
Lee Spitzley, University of Albany


Deception Detection with Bag-of-Words Features
Xunyu Chen, University of Arizona


Presenting Informational Stimuli and Using Nonverbal Behaviors to Detect Deception in Group Interaction
Xinran Wang, University of Arizona


SCAN: Cultural Analyses. Effect of Culture on Verbal Behaviour During Deception
Saiying (Tina) Ge, University of Arizona


Facial Analyses with Open Source Tools
Bradley Walls, University of Arizona


Qualitative Analysis for Deception Detection
Vincent Denault, University of Montreal

Speakers

V.S. Subrahmanian is the Dartmouth College Distinguished Professor in Cybersecurity, Technology, and Society and Director of the Institute for Security, Technology, and Society at Dartmouth. He previously served as a Professor of Computer Science at the University of Maryland from 1989-2017 where he created and headed both the Lab for Computational Cultural Dynamics and the Center for Digital International Government. He also served for 6+ years as Director of the University of Maryland's Institute for Advanced Computer Studies. Prof. Subrahmanian is an expert on big data analytics including methods to analyze text/geospatial/relational/social network data, learn behavioral models from the data, forecast actions, and influence behaviors with applications to cybersecurity and counter-terrorism. He has written five books, edited ten, and published over 300 refereed articles. He is a Fellow of the American Association for the Advancement of Science and the Association for the Advancement of Artificial Intelligence and received numerous other honors and awards. His work has been featured in numerous outlets such as the Baltimore Sun, the Economist, Science, Nature, the Washington Post, American Public Media. He serves on the editorial boards of numerous journals including Science, the Board of Directors of the Development Gateway Foundation (set up by the World Bank), SentiMetrix, Inc., and on the Research Advisory Board of Tata Consultancy Services. He previously served on DARPA's Executive Advisory Council on Advanced Logistics and as an ad-hoc member of the US Air Force Science Advisory Board.
Judee K. Burgoon is Director of Research for the Center for the Management of Information at the University of Arizona, where she holds titles as professor of communication, family studies and human development. She has authored or edited 17 books and monographs (Detecting Trust and Deception in Group Interaction, Social Signal Processing, Discovering Hidden Temporal Patterns in Behavior and Interaction, Nonverbal Communication, Interpersonal Adaptation, Small Group Communication, Mexican Americans and the Mass Media) and over 300 articles, chapters and reviews. Her current research on deception, dyadic interaction, and technologies for automated analysis of nonverbal and verbal communication has been funded by the National Science Foundation, Department of Defense Air Force, Army, Navy and ODNI, Department of Homeland Security, and Gannett Foundation, among others. She is the recipient of the highest honors given by the International Communication Association and National Communication Association and has held several offices in NCA.
Norah E. Dunbar is a Professor of Communication at University of California Santa Barbara. She teaches courses in nonverbal and interpersonal communication, communication theory, and deception detection. She is also Affiliate Faculty in the Center for Information, Technology & Society; the Center for Digital Games Research; and the Quantitative Methods in the Social Sciences program. She has received over $13 Million in research funding from agencies such as the Intelligence Advanced Research Projects Activity, the National Science Foundation, the Department of Defense, and the Center for Identification Technology Research. She has published over 65 peer-reviewed journal articles and book chapters and has presented over 100 papers at National and International conferences. Her research has appeared in top journals in her discipline including Communication Research, Communication Monographs, and Journal of Computer-Mediated Communication as well as interdisciplinary journals such as Journal of Management Information Systems and Computers in Human Behavior. She has served on the editorial board of over a dozen disciplinary journals and as the Chair of the Nonverbal Division of the National Communication Association in 2014-2016. She is the current Chair of the Communication Department at UCSB.
Dr. Jure Leskovec is an associate professor of Computer Science at Stanford University where he is a member of the InfoLab and the AI lab. He joined the department in September 2009. He is also Chief Scientists at Pinterest and an investigator at Chan Zuckerberg Biohub, where he focuses on developing new methods for analysis of biomedical data.
His general research area is applied machine learning and data science for large interconnected systems. Focuses on modeling complex, richly-labeled relational structures, graphs, and networks for systems at all scales, from interactions of proteins in a cell to interactions between humans in a society. Applications include commonsense reasoning, recommender systems, computational social science, and computational biology with an emphasis on drug discovery. This research has won several awards including a Lagrange Prize, Microsoft Research Faculty Fellowship, the Alfred P. Sloan Fellowship, and numerous best paper and test of time awards. It has also been featured in popular press outlets such as the New York Times and the Wall Street Journal. He received my bachelor's degree in computer science from University of Ljubljana, Slovenia, PhD in machine learning from Carnegie Mellon University and postdoctoral training at Cornell University. He also founded ASEF: American Slovenian Education Foundation which unites over 50 Slovenian professors all over the world and provides fellowships for students to further their education and research.
Dr. Pan Li is a postdoctoral researcher in the SNAP group lead by Prof. Jure Leskovec at Stanford University. He will join the Department of Computer Science at Purdue University as an assistant professor in Fall, 2020. Previously, he earned his master’s degree from Tsinghua University in 2015 and his PhD from the University of Illinois at Urbana-Champaign in 2019.
He holds broad research interests on topics on graph computation, graph-based machine learning, network analysis etc. He has established some fundamental theory for spectral methods over higher-order graphs. He is currently working on fundamental understanding and optimization of graph neural networks, scalable algorithms for complex graph/network computation.
Chongyang Bai is a final-year Ph.D. candidate at Dartmouth College advised by Prof. V.S. Subrahmanian. He obtained a B.S. in Computational Mathematics and B.Eng in Computer Science from University of Science and Technology of China in 2016. He spent one year as a research intern at Microsoft Research Asia and will spend this summer internship at Google Research. His research interests are multi-modal representation learning and prediction in videos. Specifically, he has studied the problems of predicting human social behaviors (e.g. persuasion, dominance, nervousness and deception) with the focus on group interaction network effects and individual audio-visual attributes. He has published several papers in top-tiered conferences and journals and served as reviewers in related AI conferences (e.g. ICME, ICMI, ICWSM) and journals (e.g. IEEE Intelligent Systems).
Dr. Dimitris Metaxas is a Distinguished Professor in the Department of Computer Science at Rutgers University, and director of the Center for Computational Biomedicine, Imaging and Modeling and the NSF IUCRC CARTA Center.
Dr. Metaxas has been conducting research towards the development of formal Data Science methods upon which AI, machine learning, computer vision, medical image analysis and computer graphics can advance synergistically.
In AI, machine learning and computer vision, new methods have been developed for understandable machine learning, real time data analytics, dynamic data driven application systems, 3D human motion analysis, human behaviors and intent recognition, scene understanding and segmentation, surveillance, object recognition, sparsity and biometrics in the wild.
In medical and biological image analysis new data science methods have been developed for material modeling and shape estimation of internal body parts (e.g., lungs) from MRI, SPAMM and CT data, a pioneering framework for cardiac motion analysis and for linking the anatomical and physiological models of the human body, cancer diagnosis, histopathology, cell tracking, cell type analysis and mouse behavior analysis.
In computer graphics, the Navier-Stokes methodology for Fluid animations in the mid 90s was introduced, based on which the water scenes in the movie “Antz” were created in 1998. Since then, new dynamic data science techniques for modeling fluid phenomena, and control theoretic techniques for automating and improving the animation of articulated (e.g., humans) objects.
Dr. Metaxas has published over 700 research articles in these areas and has graduated 56 PhD students. Dr. Metaxas has received 8 patents and numerous best paper awards for his work on vision, medical imaging and fluid modeling. The above research has been funded by NSF, NIH, ONR, AFOSR, DHS, DARPA and the ARO.
Dr Metaxas was awarded a Fulbright Fellowship in 1986, is a recipient of an NSF Research Initiation and Career awards, an ONR YIP, is a Fellow of IEEE, a Fellow of the MICCAI Society and a Fellow of the American Institute of Medical and Biological Engineers.
Jay F. Nunamaker, Jr. is Regents and Soldwedel Professor of MIS, Computer Science and Communication. He was Director of the Center for the Management of Information and the Director of the National Center for Border Security and Immigration from 2008-2015 at the University of Arizona, funded by the Department of Homeland Security (DHS) Center of Excellence program. Dr. Nunamaker was inducted into the Design Science Hall of Fame, May 2008. Dr. Nunamaker received the LEO Award for Lifetime Achievement from the Association of Information Systems (AIS) at ICIS in Barcelona, Spain, December 2002. He was elected a fellow of the AIS in 2000. He was featured in the July 1997 Forbes Magazine issue on technology as one of eight key innovators in information technology. He is widely published with an H index of greater than 84. He has produced over 400 journal articles, book chapters, books and refereed proceedings and has been a major professor for 102 Ph.D. students. His specialization is in the fields of system analysis and design, collaboration technology and deception detection. He has co-founded five spin-off companies based on his research: (1) Combinatorics which was acquired by Mathematica, 1972, (2) PLEX Corporation acquired by AT&T, 1981 (3) ULTA Systems, 1986, (4) GroupSystems Inc., 1989 and (5) Discern Science, Inc., 2011. The commercial product, GroupSystems, ThinkTank based upon Nunamaker’s research, is often referred to as the gold standard for structured collaboration systems. He was a research assistant funded by the ISDOS project in industrial engineering at the University of Michigan and an associate professor of computer science and industrial administration at Purdue University. In his career he has received 100+ million dollars as the PI or Co-PI on sponsored research at the University of Arizona, Purdue University and the University of Michigan. He founded the MIS department at the University of Arizona in 1974 and served as department head for 18 years. From 1976-1991, Nunamaker served as chairman of the ACM Curriculum Committee on Information Systems and as a committee member from 2009-2014. Dr. Nunamaker received his Ph.D. in operations research and systems engineering from Case Institute of Technology, an M.S. and B.S. in engineering from the University of Pittsburgh, and a B.S. from Carnegie Mellon University. He received his professional engineer’s license in 1965.
Miriam J. Metzger (Ph.D. University of Southern California) is a Professor in the Department of Communication at the University of California at Santa Barbara. Her research lies at the intersection of digital technology and trust, centering on how information and communication technologies alter our understandings of credibility and force us to confront new challenges in protecting our privacy. She has also published work examining the theoretical and regulatory changes brought about by emerging information and communication technologies. Her work has been published in the fields of communication, psychology, information science, computer science. Outside her home department, Dr. Metzger serves as Director of Education for the Center for Information, Technology & Society (CITS) at UCSB.