C3E

Research Context and Conference Positioning

The conference is situated within a consolidated research landscape spanning (i) systems-oriented cultural theory and cultural sociology; (ii) the methodological and epistemic debates of Digital Humanities around scale, evidence, and interpretation; (iii) complexity science and network-based approaches to cultural history; and (iv) Semantic Web traditions in knowledge organization and cultural interoperability.

Computational approaches are central not as an end in themselves, but as a means to theorize, model, and evaluate cultural complexity with explicit assumptions and interpretive accountability. Therefore, “computational” designates more than a toolkit; it signals a methodological and epistemic orientation that foregrounds:

• Formal representation of cultural knowledge: conceptual modeling, ontologies, knowledge graphs, explicit source traceability (provenance), and qualified claims (uncertainty, disagreement, approximation).
• Computational modeling and analysis: network science, temporal dynamics, simulation, statistical inference, and—where appropriate—causal or counterfactual reasoning.
• NLP for cultural discourse: from criticism and catalogues to archives and platform communication, emphasizing rhetoric, valuation, and contestation.
• Cultural data science: grounded in evaluation, interpretability, bias analysis, and epistemic accountability.
• Reproducibility and governance: documentation, FAIR principles, licensing constraints, and infrastructural sustainability.
  

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Thematic Clusters (non-exhaustive)

I) Cultural Dynamics and Historical Change

This cluster welcomes research that conceptualizes culture as a system of interacting forces unfolding across multiple scales and historical horizons. We invite work on how cultural forms, reputations, institutions, and interpretive communities emerge, stabilize, and transform over time through circulation, conflict, selection, and accumulation. Relevant topics include dynamics of visibility and invisibility, canon formation and revision, diffusion and imitation, attention cycles, and structural inequalities in access and circulation. We are especially interested in approaches that preserve historical specificity while enabling comparative or long-range analysis—through temporal modeling, event-based perspectives, or other frameworks suited to path dependence, thresholds, and turning points.

II) Cultural Infrastructures, Knowledge, and Evidence

Culture becomes knowable through infrastructures of description and preservation: catalogues, archives, standards, classification regimes, and institutional policies. This cluster invites contributions that examine how such infrastructures shape cultural memory and legibility, including their epistemic and political consequences. We welcome work on formal representations of cultural knowledge and the challenges of integrating heterogeneous sources across institutions and time: interoperability, conceptual modeling, data quality, and the management of uncertainty. We particularly value contributions that foreground evidence and traceability—provenance, versioning, missingness, and the limits of inference—so that computational claims can be evaluated as historically situated knowledge practices.

III) Cultural Discourse and Interpretation

Culture is also an ecosystem of discourse: criticism, catalogues, press, scholarship, correspondence, institutional writing, and platform-mediated conversation. This cluster invites research that investigates interpretation at scale—how meanings, valuations, and controversies circulate and become authoritative across genres, institutions, languages, and historical contexts. We welcome work that treats discourse not merely as “textual data,” but as a site where cultural power, legitimacy, and epistemic authority are negotiated.

IV) Responsibility, Data Governance, and Sustainability

Computational cultural inquiry raises questions of responsibility that are inseparable from methodological rigor. This cluster foregrounds the governance conditions under which cultural data is produced, structured, maintained, and operationalized, including legal constraints, institutional adoption, and the political consequences of automation. We invite contributions that address rights and licensing, sustainability of infrastructures, and critical analyses of bias and epistemic inequality—especially how standards, datasets, and models may reproduce historical exclusions or generate new forms of invisibility.

Submissions should engage with at least one of the following dimensions—ideally integrating several—while maintaining clarity about interpretive stakes and methodological boundaries:

• Formal representation of cultural knowledge: ontologies, event modeling, knowledge graphs, provenance, uncertainty.
• Models and metrics for cultural ecosystems: network measures, temporal modeling, diversity and visibility inequalities, thresholds.
• NLP and computational discourse analysis: stance, valuation, controversy, and the linking of textual archives and data models.
• Simulation and generative modeling: agent-based models, diffusion processes, counterfactuals, and explicit assumption modeling.
• Evaluation and responsibility: benchmarks, interpretability, bias audits, documentation, licensing, and ethical reflection.

The event is designed to converge formal representation (semantic structures), systemic modeling (complexity-sensitive methods), and critical interpretation (theory-informed reading) under explicit regimes of evaluation, uncertainty, and responsibility. Therefore, while the conference welcomes datasets, visualizations, and analytic pipelines, it is especially interested in work that leverages them to advance complexity-driven explanations of cultural ecosystems. Submissions are encouraged to articulate a complexity-oriented research question (e.g., involving feedback, emergence, non-linearity, path dependence, or multi-scale structure) and to show how computational approaches support formalization, modeling, and evaluation. Contributions that translate outputs into a coherent systemic argument—grounded in historical context and interpretive accountability—will be particularly well aligned with the conference scope.