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About this paper
Leo Torres, Ann S. Blevins, Danielle S. Bassett, Tina Eliassi-Rad
This paper presents a foundational framework for analyzing complex systems, establishing a domain-agnostic vocabulary and a structured pipeline to guide methodological choices. It empirically demonstrates how the selection of mathematical formalisms and analytical methods profoundly influences interpretations and outcomes in coauthorship and email communication datasets.
Key insights
- The optimal analytical approach for a complex system is highly context-dependent, tailored to specific system properties, available data, inherent dependencies (subset, temporal, spatial), and the research question.
- Each mathematical formalism (graphs, simplicial complexes, hypergraphs) carries distinct assumptions and captures different types of relations, necessitating careful alignment with the system's dependencies for accurate modeling.
- Converting between formalisms involves inherent information loss or the imputation of assumptions, leading to potentially divergent or even contradictory analytical insights and interpretations of system structure and behavior.
Summary by alphaXiv.
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