[Apologies if you got multiple copies of this email. This message is
sent to . If you'd like to opt out of these
announcements, information on how to unsubscribe is available at the
bottom of this email.]
******************************
(
If you do not remember your password (which is needed to change these options), you can reset it using the "Unsubscribe or Edit Options" button at the bottom of the page.
()
******************************
sent to . If you'd like to opt out of these
announcements, information on how to unsubscribe is available at the
bottom of this email.]
[Apologies if you receive multiple postings]
**Deadline Extension: January 25, 2016**
##############################
CALL FOR PAPERS
The 1st IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems
May 27 2016, Chicago Hyatt Regency, Chicago, Illinois USA.
Conference Website : http://www.lcid.cs.iit.edu/
Contact Email : parsocial@cs.iit.edu
(In conjunction with IEEE International Parallel & Distributed Processing Symposium (IPDPS))
IMPORTANT DATES
Extended Paper submission deadline : January 25, 2016
Notification of acceptance : February 14, 2016
Camera-ready papers : February 21, 2016
Workshop : May 27, 2016
##############################
ABOUT PARSOCIAL
Computational methods to represent, model and analyze problems using social information have come a long way in the last decade. Computational methods, such as social network analysis, have provided exciting insights into how social information can be utilized to better understand social processes, and model the evolution of social systems over time. We have also seen a rapid proliferation of sensor technologies, such as smartphones and medical sensors, for collecting a wide variety of social data, much of it in real time. Meanwhile, the emergence of parallel architectures, in the form of multi-core/many-core processors, and distributed platforms, such as MapReduce, have provided new approaches for large-scale modeling and simulation, and new tools for analysis. These two trends have dramatically broadened the scope of computational social systems research, and are enabling researchers to tackle new challenges. These challenges include modeling of real world scenarios with dynamic and real-time data, and formulating rigorous computational frameworks to embed social and behavioral theories. The 1st IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial) provides a platform to bring together interdisciplinary researchers from areas, such as computer science, social sciences, applied mathematics and computer engineering, to showcase innovative research in computational social systems that leverage the emerging trends in parallel and distributed processing, computational modeling, and high performance computing.
The papers selected for ParSocial will be published in the workshop proceedings. Proceedings of the workshops are distributed at the conference and are submitted for inclusion in the IEEE Xplore Digital Library after the conference. There are also plans to invite selected papers for publication in a special issue of a journal.
CALL FOR PAPERS
Areas of research interests and domains of applications include, but are not limited to:
*Large-Scale Modeling and Simulation for Social Systems*
Social network based models
Models of social interactions (e.g. influence spread, group formation, group stability, and social resilience)
Complex Adaptive System (CAS) models (e.g. modeling emergence in social systems)
Models incorporating socio-cultural factors
Novel agent based social modeling and simulation
Modeling with uncertain, incomplete social data
Models using real-time social data
Representations of social and behavioral theories in computational models
Simulation methodologies for social processes including numerical and statistical methods
Models for network dynamism
Modeling human and social elements in cyber systems (e.g. cyber-physical systems, socio-technical systems, and network centric systems)
Social Computing Algorithms for Parallel and Distributed Platforms
*Analysis of massive social data*
Algorithms for dynamic social data
Algorithms for social network analysis
Analysis methods for incomplete, uncertain social data
Social analysis methods on parallel and distributed frameworks
Social computing for emerging architectures (e.g. cloud, multi-core/many-core, GPU, and mobile computing architectures)
*Application*
Emergency management (e.g. infrastructure resilience, natural disaster management)
National security (e.g. political stability, counter-terrorism, and homeland security)
Health science (e.g. disease spread models, health informatics, and health care analytics)
Social media analytics (e.g. business analytics, political analysis, and economic analysis)
PAPER SUBMISSION
Submitted manuscripts may not exceed ten (10) single-spaced double-column pages using 10-point size font on 8.5x11 inch pages (IEEE conference style), including figures, tables, and references.
Please visit the workshop website(http://www.lcid.cs.
For additional information and questions, please send email to parsocial@cs.iit.edu and indicate “ParSocial 2016” in the subject to avoid the spam filter.
******************************
(
If you do not remember your password (which is needed to change these options), you can reset it using the "Unsubscribe or Edit Options" button at the bottom of the page.
()
******************************
No comments:
Post a Comment