q-Exponential random graphs under simple constraints exhibit sparse-dense phase transitions and triadic closure not present in standard ERGs.
Exponential random graph models
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abstract
Nowadays, exponential random graphs (ERGs) are among the most widely-studied network models. Different analytical and numerical techniques for ERG have been developed that resulted in the well-established theory with true predictive power. An excellent basic discussion of exponential random graphs addressed to social science students and researchers is given in [Anderson et al., 1999][Robins et al., 2007]. This essay is intentionally designed to be more theoretical in comparison with the well-known primers just mentioned. Given the interdisciplinary character of the new emerging science of complex networks, the essay aims to give a contribution upon which network scientists and practitioners, who represent different research areas, could build a common area of understanding.
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physics.soc-ph 1years
2026 1verdicts
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q-Exponential Random Graphs: higher-order networks from simple constraints
q-Exponential random graphs under simple constraints exhibit sparse-dense phase transitions and triadic closure not present in standard ERGs.