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ParSocial 2023 : The 7th IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (In Conjunction with IEEE IPDPS )

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Link: https://lcid.ischool.illinois.edu/parsocial/index.html
 
When May 19, 2023 - May 19, 2023
Where St. Petersburg, Florida, USA.
Submission Deadline Jan 30, 2023
Notification Due Feb 20, 2023
Final Version Due Feb 28, 2023
Categories    social network analysis   computational modeling   parallel processing   distributed computing
 

Call For Papers

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The 7th IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2023)
In Conjunction with 37th IEEE IPDPS 2023, St. Petersburg, Florida USA.
May 19, 2023
Workshop Website: https://lcid.ischool.illinois.edu/parsocial/

IMPORTANT DATES
Paper submission deadline : January 30, 2023 (extended)
Notification of acceptance : February 20, 2023
Camera-ready papers: February 28, 2023
Workshop: May 19, 2023
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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 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 while taking into account ramifications in relation to policy, ethics, privacy and other areas.

This workshop provides a platform to bring together interdisciplinary researchers from areas, such as computer science, social sciences, applied mathematics and 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. At least one of the authors of each accepted paper must register as a participant of the workshop and present the paper at the workshop.
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CALL FOR PAPERS
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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 and network dynamism (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 and real-time social data
Representations of social and behavioral theories in computational models
Simulation methodologies for social processes including numerical and statistical methods
Modeling human and social elements in cyber systems (e.g. cyber-physical systems, and socio-technical systems)

*Social Computing Algorithms for Parallel and Distributed Platforms*
Analysis of massive social data
Algorithms for dynamic social data
Algorithms for social network analysis
Machine learning/data mining-based analysis
Social Computing and Internet of Things (IoT)
Computing for social good and privacy
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 neuromorphic computing architectures)

*Application*
Domains of applications include but are not limited to:
Emergency management (e.g. infrastructure resilience, and natural disaster management)
Financial Technology (e.g. algorithmic trading, blockchains, and P2P lending)
Health science (e.g. disease spread models, health informatics, and health policy models)
Social analytics (e.g. business analytics, political influence, and economic analysis)

PAPER SUBMISSION
The workshop will accept submissions for both *regular* and *short* papers. Manuscripts for regular papers should not exceed 10 single-spaced double-column pages. Manuscripts for short papers should not exceed 4 single-spaced, double-column pages. The manuscripts should use 10-point font on 8.5 x 11 inch pages (IEEE conference style) and the page limit includes references, figures and tables.

Please visit the workshop website (https://lcid.ischool.illinois.edu/parsocial/) for details on submission.


*Workshop Organization*

**Workshop Co-Chairs**
Hien Nguyen, Associate Professor, University of Wisconsin-Whitewater, Wisconsin, USA
Suresh Subramanian, Senior Ph.D. candidate, University of Illinois at Urbana-Champaign, USA
Vairavan Murugappan, Senior Ph.D. candidate, University of Illinois at Urbana-Champaign, USA

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