Computational Social Complexity

Thematic Track @ ICCS 2023

Humans live in complex societies based on extensive cooperation, connected through social and asocial relationships. These interactions generate numerous emergent patterns. As a theoretical tool, social complexity theory provides a platform for hypothesis testing regarding the emergence of macro- and meso-level social phenomena. The track aims are to stimulate interdisciplinary research to develop complex systems-based approaches aimed at understanding social systems. We will focus on the following questions: What are the patterns in social systems that existing theories and data cannot explain? What kinds of observational and empirical data are needed to better inform the models? What new modeling techniques and methods need to be developed?

Broad topics in social complexity for which we welcome papers:

Modeling for sustainable development goals (e.g., poverty, well-being, food security, water, energy) in rapidly growing urban complex societies, focusing on the role of modeling in policy and urban planning.
Emergent phenomena of complex social systems: cooperation, self-organization, regime shifts, tipping points, and resilience.
Social Digital Twins and The Social Complexity of Digital Data (complex realism in social research, new metatheory), including novel (curated) datasets and empirical calibration and validation of computational models for understanding complex social systems.
New modeling techniques in computational social science.

Keynote: Vittorio Nespeca

University of Amsterdam & TU Delft

Building Agent-Based Models for policy support based on Qualitative Inquiry. The case of Disaster Information Management in Jakarta, Indonesia

Qualitative research is a powerful means to capture human interactions and behavior. Although there are different methodologies to develop models based on qualitative research, a methodology is missing that enables to strike a balance between the comparability across cases provided by methodologies that rely on a common and context-independent framework and the flexibility to study any policy problem provided by methodologies that focus on capturing a case study without relying on a common framework. In this keynote, I will present a methodology targeting this gap for ABMs in two stages. First, a novel conceptual framework centered on a particular policy problem is developed based on existing theories and qualitative insights from one or more case studies. Second, empirical or theoretical ABMs are developed based on the conceptual framework and generic models. This methodology is illustrated by an example application for disaster information management in Jakarta, resulting in an empirical descriptive agent-based model.

Call for Papers (Closed)

You are invited to submit a full/short paper or an extended abstract for oral presentation.

Submissions follow the standard guidelines of the conference (see here and below) and we ask for a specific structure in the discussion section of your paper [1]. The discussion section should be organized in the following way:

[optional] (Re)statement of main findings
Strengths and weaknesses of the study in relation to the relevant literature, with a particular focus on identified gaps and mismatches in results.
Meaning of the study: possible mechanisms and implications for policymakers/clinicians.
Unanswered questions and future research:
- E.g., What kinds of observational and empirical data are needed to inform (this and other) models better?
  - What (finer level) data would be ideal for informing the mechanisms considered in the model, experimental or observational?
  - What (aggregated level) data would be ideal for identifying new higher-level patterns that could emerge from the model?
- E.g., What are the patterns in social systems that the existing theories and data cannot explain?
- E.g., What new modeling techniques and methods need to be developed?

The goal is to take these elements and have two discussion sessions to identify new directions and potential connections to other fields and practices for Computational Social Complexity. The end goal of this session is to write a position paper. You can find more information about these discussion sessions in the Workshop section of this page.

The main standard guidelines of the conference are:

Full papers should have between 12/15 pages and short papers between 6/11 pages.
Manuscripts must be written in English, be based on unpublished original work, and be formatted according to the Springer LNCS template.
- Word Template
- Latex Template
Submissions should be made via EasyChair through the following link https://easychair.org/conferences/?conf=iccs20230.

Submission implies the willingness of at least one of the authors to register for the conference and attend to present their submission. To successfully submit your paper to this track, do not forget to select the Computational Social Complexity track in the EasyChair submission form.

Papers accepted to the thematic track will be published in the ICCS Proceedings in the same way as Main Track papers and are indexed by the same indices. After the conference, one paper will be nominated for a special issue of the Journal of Computational Science (JoCS). The conference organizers, together with the JoCS Editorial Board, will then select the papers which best fit the journal’s scope. Selected authors will be contacted by the conference organizers and invited to submit extended versions of their ICCS papers.

[1] Docherty, M., & Smith, R. (1999). The case for structuring the discussion of scientific papers: Much the same as that for structuring abstracts. Bmj, 318(7193), 1224-1225