Are You Up to the Challenge? Big Data and SBP 2013 Conference in DC

For the past several years I was on the SBP (Social Computing, Behavioral-Cultural Modeling and Prediction) Conference Committee and enjoyed working with a great group of colleagues with the grand finale being the conference itself. I had been responsible for the tutorials  and also helped to identify several keynoters over the years. Together, with Dr. Patrick Qiang, I also gave a tutorial. at SBP 2010.

This year, since I am on sabbatical and have been and will be out of the US a lot, I stepped down from the committee.

The SBP 2013 Conference will take place in Washington DC, April 2-5, and the keynoters are wonderful: Dr. Bernardo Huberman of HP, Dr. Michelle Gelfand of the U. of Maryland, and Dr. Myron Gutman of NSF. The tutorials should also be great.

But what really caught my interest, and the news is starting to circulate via various e-lists, is the Challenge Problem. with assistance from none other than Dr. Alex (Sandy) Pentland of MIT, who was one of the tutorial givers that I had invited for the  SBP 2011 Conference. He also was one of the plenary speakers at the Northeast Regional INFORMS Conference at UMass Amherst that I was involved in (and, I do admit, it was wonderful). Dr. Pentland had also spoken in our UMass Amherst INFORMS Speakers Series.

The deadline for the challenge problem is January 31, 2013, so time is tight!

Challenge Problem

Internationall Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction

SBP is offering a challenge problem for the second time in 2013. We organize this challenge to encourage researchers to combine the power of big data and the power of systems thinking in the field of social computing, behavioral-cultural modeling, and prediction. These datasets are brought to you by the MIT Human Dynamics Laboratory, with special thanks to professor Alex (Sandy) Pentland and his research team.

Problem Description

Cell phones afford a convenient platform to advance the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and how productivity is affected in our work spaces, and understand how rumors spread.

There remain, however, significant challenges to making mobile phones the essential tool for conducting social science research and also support mobile commerce with a solid social science foundation. Perhaps the greatest challenge is the lack of data in the public domain. There is a need for data large and extensive enough to capture the disparate facets of human behavior and interactions. Another major challenge lies in the interdisciplinary nature of conducting social science research with mobile phones. Software engineers need to work collaboratively alongside social scientists and data miners in various fields.
In an attempt to address these challenges, we have worked with the MIT Human Dynamics laboratory to release several mobile data sets in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers:

• To propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets,
• To suggest how to meaningfully extend these experiments to larger populations, or
• To develop the math that fits agent-based models or systems dynamics models to larger populations. The problem itself will be open-ended and encourage approaches from different disciplines, encompassing a range of applications using this data, including:
• Social network analysis
• Data visualization
• Simulation studies
• Predictive modeling
• Qualitative studies to supplement existing quantitative work
• Creative new applications of the data

The DataSet

Data center dynamics: The data contain the performance, behavior, and interpersonal interactions of participating employees at a Chicago-area data server configuration firm for one month. It is the first data set to contain the performance and dynamics of a real-world organization with a temporal resolution of a few seconds. The sensor data were collected by Daniel Olguin, Ben Waber, Tamie Kim, and Alex Pentland in 2007 using Sociometric Badges.
Social Evolution in an undergraduate dormitory: The data contain surveys and sensor data about the diffusion of political opinions, diet, exercise, obesity, eating habits, epidemiological contagion, depression and stress, and political opinions from 70 residents of an undergraduate dormitory. These residents represent 80% of the total population.
Friends and Family dataset: The Friends and Family experiment was designed to study (a) how people make decisions, with emphasis on the social aspects involved, and (b) how we can empower people to make better decisions using personal and social tools. The subjects were members of a young-family residential living community adjacent to a major research university in North America. All members of the community are couples, and at least one person in each family is affiliated with the university. The community is composed of over 400 residents, approximately half whom have children. The sensor data in this data set were collected using the funf open-source sensing platform for Android phones.
Reality Mining dataset: Data contain the dynamics of 75 students/faculty in the MIT Media Laboratory, and 25 incoming students at the MIT Sloan business school adjacent to the Media Laboratory. The Reality Mining experiment conducted in 2004 was the first to study community dynamics by tracking a sufficient amount people with their personal mobile phones and resulted in one of the most complete mobile data sets with rich personal behavior and interpersonal interactions. Prior to this experiment, cell phones were not powerful enough to track people.

Data access

Data is accessible from realitycommons.media.mit.edu
Users will be asked to fill out a short form and agree to privacy and data use restrictions.

Submission and Evaluation

Submissions Submissions will be evaluated based on theoretical grounding as well as use of evidence. Winners will be selected by an interdisciplinary committee of researchers and will be recognized at the conference with 1st, 2nd, and 3rd prizes. The winners will introduce the idea briefly at the conference to the audience and/or give a quick demo. Challenge organizers intend to organize winning entries into a special issue of an appropriate journal.
The submissions (6 pages) should be formatted according to the Springer-Verlag LNCS/LNAI guidelines. Sample LaTeX2e and WORD files are available from http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0.. Submissions for the challenge can be made here.

Important Dates

• Submission deadline: January 31, 2013 (23:59 PST)
• Notification of Winners: March 2, 2013

Challenge Problem Co-chairs

Nitin Agarwal, University of Arkansas, nxagarwal@ualr.edu
Wen Dong, MIT Media Lab, wdong@media.mit.edu

Prior work using this data

A bibtex file of references to prior publications using this data is available for dowload (righ-click to 'save as'): sbp2013challenge.bib
BibTeX files can be read by most bibliographic software packages well as LaTeX. Many free converters are available.

2012 challenge problem winners

Congratulations to winners of the first SBP challenge problem:

• Matthew Lease, School of Information, University of Texas at Austin "Discovering and Navigating Memes in Social Media"
• Masoud Makrehchi, Research Scientist, Thomson Reuters, Toronto, Canada "Conflict Thermometer: Predicting Social Conflicts by Analyzing Language Gap in Polarized Social Media."

The 2012 Social Computing, Behavioral-Cultural Modeling, and Prediction Conference

I am flying to the 2012 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP 2012) this Sunday.

The conference takes place at the University of Maryland, College Park.

The program is single-track and the papers are all refereed and published in a Springer volume.

I am the tutorial chair of this conference (and served in this capacity last year as well).

The tutorials take place on Monday, April 2.

The information on the tutorials is below.

Dynamic Network Analysis − Kathleen M. Carley

Dynamic network analysis enables the analyst to assess change in groups and organizations as they move through time and space on multiple dimensions. By focusing on the network of relations that connect who, what, how, why, where and when we are better able to assess and predict change and identify emergent leaders. This tutorial provides an overview of dynamic network analysis, it's value for identifying emergent leaders, and the capabilities for spatio-temporal reasoning about groups and organizations.

Kathleen M. Carley, Harvard Ph.D., is a faculty member at Carnegie Mellon University, in the School of Computer Science, the department Institute for Software Research. She is also the founder and director of the center for Computational Analysis of Social and Organizational Systems (CASOS). Her research combines cognitive science, social networks and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion and response within and among groups particularly in disaster or crisis situations. She and members of her center have developed novel tools and technologies for analyzing largescale geo-centric dynamic-networks and various multi-agent simulation systems. These tools include: ORA, a statistical and graphical toolkit for analyzing and visualizing multi-dimensional networks; AutoMap, a text-mining system for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource and task networks; CEMAP, a system for extracting networks from email and blogs; and SORASCS, a service oriented plus architecture for designing and sharing workflows in the human socio-cultural space. Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills and weaponized biological attacks; Construct an agent-based dynamic-network based nmodel for assessing network evolution and the diffusion of information and beliefs under diverse socio-demograohic and media environments; and RTE a model for examining state failure and the escalation of conflict at the city, state, nation and international as changes occur within and among red, blue and green forces.

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Crowdsourcing, Human Computation, and Collective Intelligence − Haym Hirsh

"Crowdsourcing," "human computation," and "collective intelligence" refer to various ways that information and communications technologies are bringing people and computing together to achieve outcomes that were previously beyond our individual capabilities or expectations. Google's search algorithms, Wikipedia's millions of articles, Amazon's recommendations, and open source software's multiple successes are prominent examples of the many ways in which technology and people are being brought together to exhibit new behaviors and outcomes that exceed those previously possible by people or machines in isolation. This tutorial will survey the state of the art and emerging topics in this area. Attendees will acquire knowledge of a wide range of examples in this area, a conceptual framework for relating them to each other, and an appreciation of our growing experience with how such systems can be used in unintended and undesirable ways.

Haym Hirsh is Professor of Computer Science at Rutgers University. His research focuses on crowdsourcing, data mining, human computation, and machine learning, especially targeting question that integrally involve both people and computing. From 2006-2010 he served as Director of the Division of Information and Intelligent Systems at the Nation al Science Foundation, and most recently was a visiting scholar at MIT's Center for Collective Intelligence. Haym received his BS from the Mathematics and Computer Science Departments at UCLA and his MS and PhD from the Computer Science Department at Stanford University.

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Public Health Concepts: An Introduction for Modelers − Nathaniel Osgood & Patricia L. Mabry

This tutorial is designed to introduce people with backgrounds in computer science, mathematics, engineering, physics, and related disciplines to fundamental concepts in health-related research, and provide resources and strategies for applying for National Institutes of Health (NIH) grant funding. The tutorial is aimed at health at the behavioral and social levels, rather than at biomedical and biological levels. The tutorial is aimed at systems scientists who have little or no formal background or training in the health-related disciplines, with the goal of helping prepare them to apply their methodological skills in the health domain. The tutorial will lay out the concepts necessary to facilitate the building of health related models, improve their quality, and help build cross-disciplinary relationships (i.e., bridge to health researchers). The tutorial will include: an explanation of the rationale for modeling in health; a description of classification of issues in the public health space (e.g., environmental health, communicable diseases); an appreciation for the diversity of disciplines within the health arena; and a brief discussion of specific topics of interest to the NIH. Also covered in this tutorial: important terminology issues to be aware of when working across domains; an exploration of the time dimension and its impact on health issues; a brief review of types of models and the health problems they are well suited to addressing; and major public health data types and sources that modelers should be familiar with. Presenters will also give an overview of funding agencies that support public health modeling with an emphasis on the component organizations within NIH along with specific funding opportunities at NIH and strategies for preparing grant applications. Some attention will also be paid to issues surrounding tenure and interdisciplinary work, training challenges and opportunities, and resources for learning more.

Learning Objectives:

• Understand why investigators in public health are motivated to use systems science methodologies
• Understand some basic terminology used in the public health field
• Appreciate the diversity of disciplines within health; be able to name the broad domains of health and understand their differences
• Be aware of the pitfalls of working across disciplines and how to address them proactively
• Be aware of the types of data and a few of the large data sets frequently used in health
• Name several major funders of health research and understand how their missions differ
• Be aware of a variety of journals and conferences that welcome systems science health projects
• Obtain some ideas for identifying collaborators in the health field and for developing partnerships
• Be exposed to some existing work featuring systems science methodologies applied to health problems
• Obtain resources and some explanation of the NIH grants process and specific funding opportunities
• Obtain resources on where to learn more about the above topics

Nathaniel Osgood is an Associate Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology and Division of Bioengineering at the University of Saskatchewan. His research is focused on providing tools to inform understanding of population health trends and health policy tradeoffs. This work includes both application and methodological components. On the application side, Dr. Osgood works closely with cross-disciplinary teams applying simulation modeling, smartphone-based epidemiological sensing platforms, Bayesian inference and mathematical analysis to address urgent public health challenges in both the chronic and infectious disease areas. Dr. Osgood's methodological work seek to advance the science and art of model building and epidemiological data collection for models through improved formalisms, algorithms, ubiquitous sensing frameworks, analysis techniques, and software tools. Dr. Osgood received his PhD in 1999 from MIT's Department of Electrical Engineering and Computer Science. Prior to joining the U of S faculty, he worked for many years in a number of academic and industry positions, including on industry & academic projects applying modeling to tobacco and environmental epidemiology, health informatics, and multi-framework modeling for natural resource policy-making.

Dr. Patricia L. Mabry, is a Senior Advisor in the Office of Behavioral and Social Sciences Research (OBSSR) at the National Institutes of Health (NIH) where she is facilitating the emergence of a new field that integrates systems science with health-related behavioral and social science research. Dr. Mabry’s specific achievements include issuing funding opportunity announcements in systems science (including PAR-11-314(R01) and PAR-11-315(R21) Systems Science and Health in the Behavioral and Social Sciences) and leading the development of an annual training course, the Institute on Systems Science and Health (ISSH). She co-leads (with the National Institute on Child Health and Human Development) Envision, a collaboration of modeling teams aiming to inform policy interventions to combat obesity. Envision is an activity of the National Collaborative on Childhood Obesity Research (NCCOR). Dr. Mabry was Conference Chair for the 2010 International Conference on Social Computing, Behavioral Modeling, and Prediction (SBP10) and the Organizing Chair for the 2011 Conference of the System Dynamics Society.

Dr. Mabry has authored a number of peer reviewed publications including articles in The Lancet, the American Journal of Public Health, and the American Journal of Preventive Medicine. She is Guest Editor of the upcoming special issue of Health Education and Behavior entitled, Systems Science Applications in Health Promotion and Public Health. She is a Guest Editor of the March 2010 supplement of the American Journal of Preventive Medicine entitled, Increasing Tobacco Cessation in America: A Consumer Demand Perspective and is also a Guest Editor for the 2011 Special Issue of Research in Human Development entitled, Embracing Systems Science: New Methodologies for Developmental Science.

Dr. Mabry has been recognized for her leadership in systems science and health; she was a member of the team that received the inaugural Applied Systems Thinking Prize from the Applied Systems Thinking Institute in 2008.

Dr. Mabry earned her Ph.D. in Clinical Psychology from the University of Virginia (1996) and since then has worked in small business, academia, and government.

This is the third SBP Conference that I have been involved in and I find them always very engaging professionally and intellectually and also socially.

Thanks to the wonderful sponsors who make this conference possible.

Looking Forward to the 2012 Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP) Conference

CALL FOR PARTICIPATION

Registration is now open for SBP12, the 2012 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction.

SBP12 will be held at the University of Maryland, College Park, Maryland, April 2 – April 5, 2012.

The call for participation for the SBP 2012 conference is being circulated widely.

This year's conference should be terrific, as were the previous two, which I attended.

Two years ago, Patrick Qiang and I gave a tutorial on the theme of our Fragile Networks book and last year I became the Tutorial Chair for this conference. This year I am again serving as the Tutorial Chair.

THERE ARE SOME VERY EXCITING ITEMS ON THE PROGRAM!

New in 2012 – SBP 2012 Challenge – see: http://www.umiacs.umd.edu/conferences/sbp2012/challenge.html

TUTORIALS:

Morning and afternoon tutorials are offered on Monday, April 2 (comes with registration fee, lunch included):

· Dynamic Network Analysis – Kathleen M. Carley;

· Crowdsourcing, Human Computation, and Collective Intelligence − Haym Hirsh; and

· Public Health Concepts: An Introduction for Modelers − Nathaniel Osgood & Patricia L. Mabry
To see a full description of tutorials, see: http://www.umiacs.umd.edu/conferences/sbp2012/tutorials.html


SBP12 KEYNOTE SPEAKERS:

Dr. Bobby Milstein
Fannie E. Rippel Foundation
http://rippelfoundation.org/rethink-health/rethink-health-dynamics/whos-involved/
− April 3, 8:30 − 9:15am

Dr. Patrick A. Mason
Director, Human Performance, Training, and BioSystems Directorate
Office of the Assistant Secretary of Defense for Research and Engineering
http://www.umiacs.umd.edu/conferences/sbp2012/mason.pdf
− April 4, 8:15 − 9:00am

Dr. Joshua Epstein
Professor of Emergency Medicine.
Director, Center for Advanced Modeling in the Social, Behavioral and Health Sciences (CAM)
Departments of Economics, Biostatistics, and Environmental Health
Johns Hopkins University
http://www.hopkinsmedicine.org/emergencymedicine/Faculty/JHH/EPSTEIN_joshua.html
− April 5, 8:15 − 9:00am

Please visit the conference website for further information:
http://www.umiacs.umd.edu/conferences/sbp2012/index.html

The SBP 2011 Tutorial Presentations Are Now Online!

If you missed the three excellent tutorials that were delivered this past Monday, as part of the Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP) 2011 Conference at the University of Maryland College Park, you may access the presentations online!

Tutorial 1: Toolkits for Computational Social Science: Using Honest Signals to Predict and Shape Human Responses

Alex `Sandy' Pentland, MIT

Tutorial Slides: funf Mobile Sensing System

Tutorial Slides: Influence Model

Tutorial 2: Social Network Analysis of Personal and Group Networks

Allen Tien, Medical Decision Logic

Chris McCarty, University of Florida Survey Research Center

Eric C. Jones, University of North Carolina-Greensboro

Tutorial Slides

Tutorial 3: Understanding Social Media: Tools, Applications, and Processes

Nitin Agarwal, University of Arkansas at Little Rock

Tutorial Slides

The above photos were taken at these tutorials.

Thanks again to the outstanding presenters and to the audiences for the great questions and discussions! Also, thanks to the tutorial presenters for making their lecture slides available!

Info on the 2011 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP 2011) is Now Online!

I am delighted to announce that the 2011 SBP conference program, along with tutorial information, and keynotes, is now posted online on the conference website.

The program committee has worked very hard and the conference speaker lineup is terrific. I might add that this conference has single track talks and all the talks are based on rigorously reviewed papers, which will appear in a Springer Proceedings volume, which is now in press.

The Keynote speakers and their keynotes are:

Kimberly Thompson
Kid Risk, Inc.
Using Models to Inform Policy: Insights from Modeling the Complexities of Global Polio Eradication
- March 29, 8:30-9:15am

Peter Cramton
University of Maryland
Medicare Auctions: A Case Study of Market Design in Washington, DC
- March 29, 1:00-1:45pm

Herbert Gintis
Central European University and the Santa Fe Institute
Agent-based Models of Complex Dynamical Systems of Market Exchange
- March 30, 1:00-1:45pm

Sarit Kraus
Bar-Ilan University and University of Maryland
Agents that Negotiate Proficiently with People
- March 31, 8:15-9:00am

The Tutorials take place on March 28, 2011 and the presenters and their tutorials are:

Tutorial, March 28, 8:30am–12:30pm:

Toolkits for Computational Social Science: Using Honest Signals to Predict and Shape Human Responses
Alex `Sandy' Pentland, MIT

Tutorial, March 28, 2:00–5:30pm:

Social Network Analysis of Personal and Group Networks
Allen Tien, Medical Decision Logic
Chris McCarty, University of Florida Survey Research Center
Eric C Jones, University of North Carolina-Greensboro

Tutorial, March 28, 2:00–5:30pm:

Behavioral Informatics: Data Management and Mining Techniques Enabling Computational Behavioral Science Jaideep Srivastava, University of Minnesota

Come and learn about topics ranging from health issues via Twitter to optimization-based influencing of village social networks in counterinsurgencies to location privacy protection on social networks and even to promoting coordination for disaster relief -- from crowdsourcing to coordination!

There will also be cross-fertilization roundtables.

Registration will soon be open!

2011 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP) Call for Papers

Mark your calendars!

Information on the 2011 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction is now available on the conference website! The conference will take place March 29-31, 2011 at the University of Maryland College Park, with tutorials on March 28.

I enjoyed last year's conference so much at which Dr. Patrick Qiang and I presented a tutorial on Fragile Networks: Identifying Vulnerabilities and Synergies in an Uncertain World that I agreed to be the tutorial chair at this year's conference.

This conference is truly interdisciplinary and the researchers and practitioners that we met last year were fascinating to interact with.

Call for Papers and Posters

Papers or posters are solicited on research issues, theories, and applications. Topics of interests include, but are not limited to:

1. Military and security applications of SBP
   1. Group formation and evolution in the political context
   2. Technology and flash crowds
   3. Networks and political influence
   4. Information diffusion
   5. Group representation and profiling
2. Health applications of SBP
   1. Social network analysis to understand health behavior
   2. Modeling of health policy and decision making
   3. Modeling of behavioral aspects of infectious disease spread
   4. Intervention design and modeling for behavioral health
3. Basic research on sociocultural and behavioral processes using SBP
   1. Group interaction and collaboration
   2. Group formation and evolution
   3. Group representation and profiling
   4. Cultural patterns and representation
   5. Social conventions and social contexts
   6. Influence process and recognition
   7. Public opinion representation
   8. Viral marketing and information diffusion
   9. Psycho-cultural situation awareness
4. Methodological issues in SBP
   1. Verification and validation
   2. Sensitivity analysis
   3. Matching technique or method to research questions
   4. Metrics and evaluation
   5. Methodological innovation
   6. Model federation and integration
   7. Limitations of and barriers to SBP
   8. Research gaps and opportunities

The full call for papers can also be downloaded here in pdf format and the deadline for paper submissions is November 6, 2010.

For the 2011 SBP Conference Committee click here.