Improving exponential-family random graph models for bipartite networks | Paper Citation Record

Observation f17d785e-1ed7-4364-89ab-abd087c5a2dc · outbound

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Improving exponential-family random graph models for bipartite networks The duality of persons and groups.Soc Forces, 53(2):181–190, 1974

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Observation 17528110-16a8-4fe3-b2c0-46fe8c0d0ba4 · outbound

This paper cites Neal, Annabell Cadieux, Diego Garlaschelli, Nicholas J.

Improving exponential-family random graph models for bipartite networks Neal, Annabell Cadieux, Diego Garlaschelli, Nicholas J

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Improving exponential-family random graph models for bipartite networks Exponential random graph models for multilevel networks.Soc Netw, 35(1):96–115, 2013

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Improving exponential-family random graph models for bipartite networks Basic notions for the analysis of large two- mode networks.Soc Netw, 30(1):31–48, 2008

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Improving exponential-family random graph models for bipartite networks The dual-projection approach for two-mode networks.Soc Netw, 35(2):204–210, 2013

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Improving exponential-family random graph models for bipartite networks Centrality and the dual-projection approach for two-mode social network data.Method Innov, 9:2059799116630662, 2016

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Improving exponential-family random graph models for bipartite networks Granovetter

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Observation 9fc5aae8-b28a-4538-a79d-a8d8a803de68 · outbound

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Improving exponential-family random graph models for bipartite networks Weisstein

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Improving exponential-family random graph models for bipartite networks Small worlds among interlocking directors: Network structure and distance in bipartite graphs.Comput Math Organ Theory, 10(1):69–94, 2004

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Improving exponential-family random graph models for bipartite networks Triadic closure in two-mode networks: Redefining the global and local clustering coefficients

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Improving exponential-family random graph models for bipartite networks Modelling the evolution of a bipartite network—peer referral in inter- locking directorates.Soc Netw, 34(3):309–322, 2012

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Observation d434b6e9-c926-4a41-92bb-9b9e7a9e902c · outbound

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Improving exponential-family random graph models for bipartite networks Transitivity and degree assortativity explained: The bipartite structure of social networks.Phys Rev E, 101(5):052305, 2020

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Observation 8ca43713-1521-41a3-89df-9ae214056829 · outbound

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Improving exponential-family random graph models for bipartite networks The role of bipartite structure in R&D collaboration networks

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Improving exponential-family random graph models for bipartite networks Structural Analysis in the Social Sciences

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Observation 8058ff82-f4b4-4e4a-8c5e-fc30695fe673 · outbound

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Improving exponential-family random graph models for bipartite networks Social network modeling.Annu Rev Stat Appl, 5:343– 369, 2018

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Observation ea20fe90-ce3b-4555-af81-bc9277db8f22 · outbound

This paper cites Koskinen.

Improving exponential-family random graph models for bipartite networks Koskinen

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Improving exponential-family random graph models for bipartite networks Exponential random graph models

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Observation d7de9a2e-0c66-46d0-9cc4-82bed5faeafb · outbound

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Improving exponential-family random graph models for bipartite networks The statistical physics of real-world networks.Nat Rev Phys, 1(1):58–71, 2019

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Observation 90854f72-9b65-415c-ba9d-0e64f089b7f2 · outbound

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Improving exponential-family random graph models for bipartite networks A survey on exponential random graph models: an application perspective.PeerJ Comput Sci, 6:e269, 2020

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Observation 5cb17968-b292-4ba6-8c9c-fedb3871be9a · outbound

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Improving exponential-family random graph models for bipartite networks Generating synthetic power grids using expo- nential random graph models.PRX Energy, 3(2):023005, 2024

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Observation 4165c803-6a7e-4668-b88a-ce23ac19999c · outbound

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Improving exponential-family random graph models for bipartite networks Exponential random graph (p*) models for affiliation networks.Soc Netw, 31(1):12–25, 2009

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Improving exponential-family random graph models for bipartite networks Exponential random graph model specifications for bipartite networks—a dependence hierarchy.Soc Netw, 35(2):211–222, 2013

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Observation 35a0aa8d-e6ec-4a4b-b1a5-f2c87ed3ba38 · outbound

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Improving exponential-family random graph models for bipartite networks Exponential random graph model extensions: Models for multiple networks and bipartite net- works

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Observation c4b93642-bb73-4f9b-a4d5-fc79c4b1cdd6 · outbound

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Improving exponential-family random graph models for bipartite networks Modeling Homophily in Exponential-Family Random Graph Models for Bipartite Networks

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Observation 257b35b9-07df-4eae-8136-87de9a5049d7 · outbound

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Improving exponential-family random graph models for bipartite networks Pattison and T.A.B

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Improving exponential-family random graph models for bipartite networks Constrained Monte Carlo maximum likelihood for dependent data.J R Stat Soc B, 54(3):657–683, 1992

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Improving exponential-family random graph models for bipartite networks Unresolved cited work

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Improving exponential-family random graph models for bipartite networks Computational statistical methods for social network models.J Comput Graph Stat, 21(4):856–882, 2012

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Improving exponential-family random graph models for bipartite networks Auxiliary parameter MCMC for exponential random graph models.J Stat Phys, 165(4):740–754, 2016

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Improving exponential-family random graph models for bipartite networks Fast maximum likeli- hood estimation via equilibrium expectation for large network data.Sci Rep, 8(1):11509, 2018

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Improving exponential-family random graph models for bipartite networks A Simple Algorithm for Scalable Monte Carlo Inference

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Observation 357959f5-4172-41af-b3e0-51140a7dc3be · outbound

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Improving exponential-family random graph models for bipartite networks Assessing degeneracy in statistical models of social networks

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Improving exponential-family random graph models for bipartite networks Unresolved cited work

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Improving exponential-family random graph models for bipartite networks Removing phase transitions from Gibbs measures

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Improving exponential-family random graph models for bipartite networks Instability, sensitivity, and degeneracy of discrete exponential families.J Am Stat Assoc, 106(496):1361–1370, 2011

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Improving exponential-family random graph models for bipartite networks Estimating and understanding exponential random graph models.Ann Stat, 41(5):2428–2461, 2013

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Improving exponential-family random graph models for bipartite networks Consistent structure estimation of exponential-family random graph models with block structure.Bernoulli, 26(2):1205–1233, 2020

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Improving exponential-family random graph models for bipartite networks Practical network modeling via tapered exponential-family random graph models.J Comput Graph Stat, 32(2):388–401, 2023

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Improving exponential-family random graph models for bipartite networks Unresolved cited work

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Improving exponential-family random graph models for bipartite networks Koskinen and G

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Improving exponential-family random graph models for bipartite networks Unresolved cited work

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Improving exponential-family random graph models for bipartite networks Overcoming near-degeneracy in the autologistic actor attribute model

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Observation 15ed59fc-f0db-4be6-8e30-6e5838b4c5d6 · outbound

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Improving exponential-family random graph models for bipartite networks Hunter and Mark S

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This paper cites Melbourne School of Psychological Sciences, The University of Melbourne, 2014.http://www.melnet.org.au/s/MPNetManual.pdf.

Improving exponential-family random graph models for bipartite networks Melbourne School of Psychological Sciences, The University of Melbourne, 2014.http://www.melnet.org.au/s/MPNetManual.pdf

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Improving exponential-family random graph models for bipartite networks Unresolved cited work

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Improving exponential-family random graph models for bipartite networks Unresolved cited work

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Observation fb7eab04-0933-4b4c-8e12-0d6776a13fef · outbound

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Improving exponential-family random graph models for bipartite networks Handcock, David R

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Observation 95df866e-db91-4b78-9a18-51858c6959b4 · outbound

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Improving exponential-family random graph models for bipartite networks ergm: A package to fit, simulate and diagnose exponential-family models for networks.J Stat Softw, 24(3):1–29, 2008

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Observation a0f1a653-36e8-42a0-b12f-b9afdb624c4a · outbound

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Improving exponential-family random graph models for bipartite networks Hummel, David R

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Observation fbc0de4d-b421-48fa-b8f9-76e4a5efa820 · outbound

This paper cites Handcock, David R.

Improving exponential-family random graph models for bipartite networks Handcock, David R

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Observation 251450ec-a2eb-4cba-bde4-685ee3d84218 · outbound

This paper cites Handcock, David R.

Improving exponential-family random graph models for bipartite networks Handcock, David R

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Observation 71ad954c-069a-4c28-9cc2-62f7f42e510e · outbound

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Improving exponential-family random graph models for bipartite networks Krivitsky, David R

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Observation c58e2b79-c2bd-4d21-ac96-3b6570e8487a · outbound

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Improving exponential-family random graph models for bipartite networks ergm 4: Computational Improvements

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Observation af9a85f0-4e4e-4430-a86b-4a1b141192d7 · outbound

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Improving exponential-family random graph models for bipartite networks Bergm: Bayesian exponential random graphs in R.J Stat Softw, 61(2):1–25, 2014

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Improving exponential-family random graph models for bipartite networks Statistical network analysis with Bergm.J Stat Softw, 104(1):1–23, 2022

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Improving exponential-family random graph models for bipartite networks Sustainable energy governance in South Tyrol (Italy): A probabilistic bipartite network model.J Clean Prod, 221:854–862, 2019

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Improving exponential-family random graph models for bipartite networks Local structural properties and attribute characteristics in 2-mode networks: p* models to map choices of theater events.J Math Sociol, 32(3):204–237, 2008

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Observation 7e6d7594-cf3d-4eb3-8d54-e57f447d5c32 · outbound

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Improving exponential-family random graph models for bipartite networks Benton and Jihae You

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Observation 99609a0d-5704-4c91-bd74-d09470e0e45c · outbound

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Improving exponential-family random graph models for bipartite networks Adapting to sea-level rise: Centralization or decentralization in polycentric governance systems?Policy Stud J, 50(1):143–175, 2022

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.152826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cdb260f-0aa3-48ee-b061-4e78d551ae9c · outbound

This paper cites Watts and Steven H.

Improving exponential-family random graph models for bipartite networks Watts and Steven H

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.156947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 163f4ea2-00c7-4c22-8edf-b695d229ce7d · outbound

This paper cites Why social networks are different from other types of networks.Phys Rev E, 68(3):036122, 2003.

Improving exponential-family random graph models for bipartite networks Why social networks are different from other types of networks.Phys Rev E, 68(3):036122, 2003

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.161156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3852d128-5393-4441-ac11-23b4f6b67775 · outbound

This paper cites Comparing the real-world performance of exponential-family random graph models and latent order logistic models for social network analysis.J R Stat Soc A, 185(2):566–587, 2022.

Improving exponential-family random graph models for bipartite networks Comparing the real-world performance of exponential-family random graph models and latent order logistic models for social network analysis.J R Stat Soc A, 185(2):566–587, 2022

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.165427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64ad0b80-c119-4fcc-b875-b9a90d9a3504 · outbound

This paper cites A New Generative Statistical Model for Graphs: The Latent Order Logistic (LOLOG) Model.

Improving exponential-family random graph models for bipartite networks A New Generative Statistical Model for Graphs: The Latent Order Logistic (LOLOG) Model

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.169596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ff92e5-5ddb-4998-81ec-1f467c1ca108 · outbound

This paper cites Who speaks up to whom? a relational approach to employee voice.Soc Netw, 33(4):303–316, 2011.

Improving exponential-family random graph models for bipartite networks Who speaks up to whom? a relational approach to employee voice.Soc Netw, 33(4):303–316, 2011

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.174050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf07f707-ab8f-4b0d-a4dd-6ba6b70eaf35 · outbound

This paper cites Social context, spatial structure and social network structure.Soc Netw, 34(1):32–46, 2012.

Improving exponential-family random graph models for bipartite networks Social context, spatial structure and social network structure.Soc Netw, 34(1):32–46, 2012

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.178281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19aba213-1b10-456c-9c2c-a60a64309712 · outbound

This paper cites Gygax, and Peng Wang.

Improving exponential-family random graph models for bipartite networks Gygax, and Peng Wang

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.182548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11011952-fc02-4fda-96fd-71439cdea491 · outbound

This paper cites Goodreau.

Improving exponential-family random graph models for bipartite networks Goodreau

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.186707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 341ffb7c-9e88-424b-bf7e-3379a069f415 · outbound

This paper cites Relationship patterns in the 19th century: The friendship network in a German boys’ school class from 1880 to 1881 revisited.Soc Netw, 37:1–13, 2014.

Improving exponential-family random graph models for bipartite networks Relationship patterns in the 19th century: The friendship network in a German boys’ school class from 1880 to 1881 revisited.Soc Netw, 37:1–13, 2014

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.190866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e918ddb-9e8e-4ba1-b24b-f5cf3388d010 · outbound

This paper cites Social networks and spatial configuration—how office layouts drive so- cial interaction.Soc Netw, 34(1):47–58, 2012.

Improving exponential-family random graph models for bipartite networks Social networks and spatial configuration—how office layouts drive so- cial interaction.Soc Netw, 34(1):47–58, 2012

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.194886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f094638-c92d-4c33-901a-48be972240bd · outbound

This paper cites Unpacking reputational power: Intended and unintended determinants of the assessment of actors’ power.Soc Netw, 42:60–71, 2015.

Improving exponential-family random graph models for bipartite networks Unpacking reputational power: Intended and unintended determinants of the assessment of actors’ power.Soc Netw, 42:60–71, 2015

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.199111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b03ef35-6cc6-498d-95a8-d4ca5eb5282f · outbound

This paper cites A comparative study of social network models: Network evolution models and nodal attribute models.Soc Netw, 31(4):240–254, 2009.

Improving exponential-family random graph models for bipartite networks A comparative study of social network models: Network evolution models and nodal attribute models.Soc Netw, 31(4):240–254, 2009

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.203297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73b83568-6834-4c69-a7f1-e9b36f3c13dd · outbound

This paper cites Online collective identity: The case of the environmental movement.Soc Netw, 33(3):177–190, 2011.

Improving exponential-family random graph models for bipartite networks Online collective identity: The case of the environmental movement.Soc Netw, 33(3):177–190, 2011

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.207542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a6defaf-f0ca-408c-bffd-ede54b0be1fd · outbound

This paper cites A p* primer: logit models for social networks.

Improving exponential-family random graph models for bipartite networks A p* primer: logit models for social networks

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.211628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cac1ae3-4243-4a59-ba79-2cc0e99f0e25 · outbound

This paper cites Exponential random graph model parameter estimation for very large directed networks.PLoS One, 15(1):e0227804, 2020.

Improving exponential-family random graph models for bipartite networks Exponential random graph model parameter estimation for very large directed networks.PLoS One, 15(1):e0227804, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.215606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ccbb579-35f4-42e7-93ad-1b91fcbf20e9 · outbound

This paper cites Differential impact of directors’ social and financial capital on corporate interlock formation.

Improving exponential-family random graph models for bipartite networks Differential impact of directors’ social and financial capital on corporate interlock formation

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.219844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9540d3ff-df20-48b1-a259-0db4ece69afe · outbound

This paper cites Geodesic cycle length distributions in delusional and other social networks.J Soc Struct, 21(1):35–76, 2020.

Improving exponential-family random graph models for bipartite networks Geodesic cycle length distributions in delusional and other social networks.J Soc Struct, 21(1):35–76, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.224250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb56182e-05de-4925-be2a-4f81f666a8df · outbound

This paper cites Geodesic cycle length distributions in fictional character networks.

Improving exponential-family random graph models for bipartite networks Geodesic cycle length distributions in fictional character networks

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Resolution: verified exact; local_arxiv, observed 2026-08-09T14:12:44.659104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d7b053ad-a294-41e5-9aaf-f049358b2791 · outbound

This paper cites Comment on geodesic cycle length distributions in delusional and other social networks.J Soc Struct, 21(1):77–93, 2020.

Improving exponential-family random graph models for bipartite networks Comment on geodesic cycle length distributions in delusional and other social networks.J Soc Struct, 21(1):77–93, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.232953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dabc80b8-8a42-4f6a-90b8-f3ab70f0bd35 · outbound

This paper cites Stochastic weighted graphs: Flexible model specification and simulation.Soc Netw, 49:37–47, 2017.

Improving exponential-family random graph models for bipartite networks Stochastic weighted graphs: Flexible model specification and simulation.Soc Netw, 49:37–47, 2017

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.236513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a75840f9-99f7-44da-a543-77113ce31c65 · outbound

This paper cites Pattison, Garry L.

Improving exponential-family random graph models for bipartite networks Pattison, Garry L

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.240091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85cb2019-837a-405f-b928-780291399261 · outbound

This paper cites Neighborhood–based models for social networks.Sociol Methodol, 32(1):301–337, 2002.

Improving exponential-family random graph models for bipartite networks Neighborhood–based models for social networks.Sociol Methodol, 32(1):301–337, 2002

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Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.243793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3474325b-b5ff-42e8-8bdf-ac974473fb1c · outbound

This paper cites Building models for social space: Neighourhood-based models for social networks and affiliation structures.Math & Sci Hum, 42(168):11–29, 2004.

Improving exponential-family random graph models for bipartite networks Building models for social space: Neighourhood-based models for social networks and affiliation structures.Math & Sci Hum, 42(168):11–29, 2004

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.660444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7f8fdc7b-5894-4cad-b709-375e810133d3 · outbound

This paper cites Hunter, Steven M.

Improving exponential-family random graph models for bipartite networks Hunter, Steven M

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.647473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d3aa59e7-6bd8-4233-bda5-a8c46d2e7612 · outbound

This paper cites Extending ERGM functionality within statnet: Building custom user terms.https://statnet.org/workshop-ergm-userterms/ergm.userterms_tutorial .pdf, 2019.

Improving exponential-family random graph models for bipartite networks Extending ERGM functionality within statnet: Building custom user terms.https://statnet.org/workshop-ergm-userterms/ergm.userterms_tutorial .pdf, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.634259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9b014750-5a08-4d2c-947b-fc31ae8eb149 · outbound

This paper cites An efficient algorithm for enumerating chordless cycles and chordless paths.

Improving exponential-family random graph models for bipartite networks An efficient algorithm for enumerating chordless cycles and chordless paths

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.621247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1fdc5dc-00df-4524-bc6e-664e3ff498e7 · outbound

This paper cites R Foundation for Statistical Com- puting, Vienna, Austria, 2022.

Improving exponential-family random graph models for bipartite networks R Foundation for Statistical Com- puting, Vienna, Austria, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.608215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a7387bb0-6703-4fc0-b22f-670e6e2db484 · outbound

This paper cites The igraph software package for complex network research.InterJournal, Complex Systems:1695, 2006.

Improving exponential-family random graph models for bipartite networks The igraph software package for complex network research.InterJournal, Complex Systems:1695, 2006

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.595014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 47e37ab4-3472-4a9e-96cd-42e754cd127d · outbound

This paper cites igraph enables fast and robust network analysis across programming languages.

Improving exponential-family random graph models for bipartite networks igraph enables fast and robust network analysis across programming languages

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:44.270712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94105339-674f-4c1d-8909-83411d958b07 · outbound

This paper cites Springer-Verlag, New York, 2016.

Improving exponential-family random graph models for bipartite networks Springer-Verlag, New York, 2016

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.582046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 65332dae-7ff5-496f-9438-e606382c6705 · outbound

This paper cites Specification of exponential-family random graph models: Terms and computational aspects.J Stat Softw, 24(4):1–24, 2008.

Improving exponential-family random graph models for bipartite networks Specification of exponential-family random graph models: Terms and computational aspects.J Stat Softw, 24(4):1–24, 2008

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.568778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c09736b5-82cb-458c-a07e-feb5c8e4e45b · outbound

This paper cites University of Chicago Press, 1941.

Improving exponential-family random graph models for bipartite networks University of Chicago Press, 1941

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.555208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9aff407e-86a1-4fff-b5e5-34a55e8afffb · outbound

This paper cites Krivitsky and Mark S.

Improving exponential-family random graph models for bipartite networks Krivitsky and Mark S

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.542187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8dd6352d-db46-4858-8f40-5748825daa29 · outbound

This paper cites Krivitsky and Mark S.

Improving exponential-family random graph models for bipartite networks Krivitsky and Mark S

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.528766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c604086c-a584-4256-b19c-4c41167a307b · outbound

This paper cites A dynamic model for the mutual constitution of individuals and events.J Complex Netw, 10(2):cnac004, 03 2022.

Improving exponential-family random graph models for bipartite networks A dynamic model for the mutual constitution of individuals and events.J Complex Netw, 10(2):cnac004, 03 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.516390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0954e151-f6cc-4e47-b9c5-4d9d0e797473 · outbound

This paper cites Bipartite exponential random graph models with nodal random effects.

Improving exponential-family random graph models for bipartite networks Bipartite exponential random graph models with nodal random effects

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.503764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 672cceeb-aae2-46f3-b44c-91545776ae19 · outbound

This paper cites Measuring knowledge and experience in two mode temporal networks.Soc Netw, 55:63–73, 2018.

Improving exponential-family random graph models for bipartite networks Measuring knowledge and experience in two mode temporal networks.Soc Netw, 55:63–73, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.491173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 80cf4e2f-9668-4b83-9d91-09435855bb3b · outbound

This paper cites texreg: Conversion of statistical model output in R to L ATEX and HTML tables.J Stat Softw, 55(8):1–24, 2013.

Improving exponential-family random graph models for bipartite networks texreg: Conversion of statistical model output in R to L ATEX and HTML tables.J Stat Softw, 55(8):1–24, 2013

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.478406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 119a665f-e5c8-4a46-bc34-2f5b7d0f9a68 · outbound

This paper cites Interpretation of gw-degree estimates in ERGMs, June 2016.https://doi.org/10.6084/m9.figshare.3465020.v1.

Improving exponential-family random graph models for bipartite networks Interpretation of gw-degree estimates in ERGMs, June 2016.https://doi.org/10.6084/m9.figshare.3465020.v1

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Resolution: verified exact; doi, observed 2026-08-09T14:12:44.592313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 44ce9157-1df8-4763-97e4-fba457fc3190 · outbound

This paper cites gwdegree: Improving interpretation of geometrically-weighted degree estimates in exponential random graph models.J Open Source Softw, 1(3):36, 2016.

Improving exponential-family random graph models for bipartite networks gwdegree: Improving interpretation of geometrically-weighted degree estimates in exponential random graph models.J Open Source Softw, 1(3):36, 2016

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.464819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0d439bb9-d744-4dbc-a6ba-0b64bfe2df1c · outbound

This paper cites Comment on geodesic cycle length distributions in delusional and other social net- works.

Improving exponential-family random graph models for bipartite networks Comment on geodesic cycle length distributions in delusional and other social net- works

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:12:45.451306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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