[hpc-announce] CFP: IPDPS ParSocial 2024 - 8th IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems

[Subramanian, Suresh]

[Apologies if you receive multiple postings]
###############################################################################################
8th IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems (ParSocial 2024)
In Conjunction with 38th IEEE IPDPS 2024, San Francisco, California USA.
May 31, 2024,
Workshop Website: https://lcid.ischool.illinois.edu/parsocial/

IMPORTANT DATES
Paper submission deadline: Feb. 16, 2024
Notification of acceptance:   Feb. 23, 2024
Camera-ready papers:         Feb. 29, 2024
Workshop:                          May. 31, 2024
###############################################################################################

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.
-----------------------------------------------------------
CALL FOR PAPERS
-----------------------------------------------------------

Areas of research interests and domains of applications include, but are NOT LIMITED to:

Social Computing Algorithms

  *   Algorithms for massive and dynamic social data
  *   Social sensing
  *   Big Cross-Modal Social Media Data Analytics
  *   Novel machine learning/data mining-based techniques
  *   Algorithms and novel techniques to accelerate training/prediction of deep learning, neural networks and large language models (LLMs) for social computing
  *   Social Internet of Things (SIoT)
  *   Computing for social good and privacy
  *   Social network analysis with incomplete, uncertain social data
  *   Social computing for heterogeneous architectures (e.g. cloud, multi-core/many-core, GPU, and neuromorphic computing architectures)
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)
Applications

  *   Emergency management (e.g. infrastructure resilience, and natural disaster management)
  *   Financial Technology (e.g. algorithmic trading, blockchains, and P2P lending)
  *   Health science (e.g. health informatics and health policy models)
  *   Social analytics (e.g. business analytics and economic analysis)
  *   Political science (e.g. political influence, fake news and election predictions)

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
  *   Jeremy Thompson, Associate Professor, Washington State University Everett, USA.
Student Co-Chairs/Organizers:

  *   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