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<p>Martin (2020) describes a misinterpretation of exponential random graph (ERGM) parameters in my contribution (Stivala 2020), with the use of this parametric model obscuring, rather than illuminating, the data. He suggests that this is symptomatic of a trend in the social networks community towards a methodological monoculture focussed on the use of ERGMs. In this Reply I try to clarify how this situation arose in this specific case, and address some more general issues Martin raises, including the use of nodal covariates, what we can learn from ERGMs, and methodological monoculturalism in social network research.</p>
</abstract>

Martin (2020) describes a misinterpretation of exponential random graph (ERGM) parameters in my contribution (Stivala 2020), with the use of this parametric model obscuring, rather than illuminating, the data. He suggests that this is symptomatic of a trend in the social networks community towards a methodological monoculture focussed on the use of ERGMs. In this Reply I try to clarify how this situation arose in this specific case, and address some more general issues Martin raises, including the use of nodal covariates, what we can learn from ERGMs, and methodological monoculturalism in social network research.

Reply to “Comment on Geodesic Cycle Length Distributions in Delusional and Other Social Networks”

Journal of Social Structure

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Martin (2020) describes a misinterpretation of exponential random graph (ERGM) parameters in my contribution (Stivala 2020), with the use of this parametric...

Reply to “Comment on Geodesic Cycle Length Distributions in Delusional and Other Social Networks”

Article Category: research-article

Pubblicato online: 01 ott 2020

Pagine: 94 - 106

DOI: https://doi.org/10.21307/joss-2020-004

Parole chiave
Geodesic cycle, Exponential random graph model, ERGM, dk-series random graphs, Social networks, Fictional networks, Dissociative identity disorder

© 2019 Alex Stivala; et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Reply to “Comment on Geodesic Cycle Length Distributions in Delusional and Other Social Networks”

Article Category: research-article

Pubblicato online: 01 ott 2020

Pagine: 94 - 106

DOI: https://doi.org/10.21307/joss-2020-004

Parole chiaveGeodesic cycle, Exponential random graph model, ERGM, dk-series random graphs, Social networks, Fictional networks, Dissociative identity disorder

© 2019 Alex Stivala; et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Parole chiave
Geodesic cycle, Exponential random graph model, ERGM, dk-series random graphs, Social networks, Fictional networks, Dissociative identity disorder