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01-12-2023 | Original Article

The gap between public evaluations and interactional status in social networks

Author: Neha Gondal

Published in: Social Network Analysis and Mining | Issue 1/2023

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Abstract

The article explores the discrepancies between public evaluations and interactional status in social networks, focusing on the mechanisms that drive these inconsistencies. It delves into the formation of status hierarchies through the accumulation of deference in interactions and the increasing ubiquity of evaluations based on peer surveys. The author proposes a creative use of ERGM fit statistics to quantify the degree of convergence or divergence between these two measures of status. The study uses data on faculty hiring networks in sociology and peer evaluations from US News and World Report to test this framework, highlighting the potential implications of discrepancies in status perceptions. This analysis provides a comprehensive understanding of the complex interplay between public evaluations and interactional status, contributing valuable insights to the field of social network analysis.

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Appendix
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Footnotes
1
The structural reciprocity parameter needs to be included in the models to be able to include reciprocity based on nodal attributes. Rather than all ties being independent of each other, the inclusion of the reciprocity parameter implies that only ties that occur between the same nodes are interdependent.
 
2
Although multicollinearity could be an issue in these models, tests demonstrate this to not be a concern. Multicollinearity in ERGMs is generally assessed in two ways: (1) the variance inflation factor (VIF) of coefficients and (2) the stability of model coefficients (Duxbury 2018). The highest VIF for estimates in Models 1–4 were below concerning levels. Rerunning Models 1–4 multiple times also yielded highly stable coefficients.
 
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Metadata
Title
The gap between public evaluations and interactional status in social networks
Author
Neha Gondal
Publication date
01-12-2023
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2023
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-023-01099-4

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