Sensitivity analysis for network observations with applications to inferences of social influence effects
Bibliographic Data
| ID | 6161383 |
|---|---|
| Authors | R Xu (0000-0002-5832-9226, University of Connecticut, corresponding author), K A Frank (0000-0002-6116-5509, Michigan State University) |
| Year | 2020 |
| Volume | 9 |
| Issue | 1 |
| Pages | 73-98 |
| Publication date | 2020-10-19 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Network Science (JOURNAL) |
| Journal identifiers | ISSN: 2050-1250 • E-ISSN: 2050-1242 |
| Publisher | Cambridge University Press (PUBLISHER • US) |
| DOI | 10.1017/nws.2020.36 |
| OpenAlex | W3093643191 |
| Language | EN |
| Citations received | 1 |
| References cited | 76 |
The validity of network observations is sometimes of concern in empirical studies, since observed networks are prone to error and may not represent the population of interest. This lack of validity is not just a result of random measurement error, but often due to systematic bias that can lead to the misinterpretation of actors’ preferences of network selections. These issues in network observations could bias the estimation of common network models (such as those pertaining to influence and selection) and lead to erroneous statistical inferences. In this study, we proposed a simulation-based sensitivity analysis method that can evaluate the robustness of inferences made in social network analysis to six forms of selection mechanisms that can cause biases in network observations—random, homophily, anti-homophily, transitivity, reciprocity, and preferential attachment. We then applied this sensitivity analysis to test the robustness of inferences for social influence effects, and we derived two sets of analytical solutions that can account for biases in network observations due to random, homophily, and anti-homophily selection
Econometrics · Homophily · Inference · Machine learning · Reciprocity (cultural anthropology · Robustness (evolution · Selection bias · Sensitivity (control systems · Social network (sociolinguistics · Statistics · Transitive relation · Complex Network Analysis Techniques · Computer Science · Mathematics · Opinion Dynamics and Social Influence · Psychology · Social Capital and Networks · Social Psychology · Artificial Intelligence
Imputation of Missing Network Data
Social Network Analysis
Small Worlds and Regional Innovation
Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks
Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome
Modeling social networks from sampled data
Opinion Leadership and Social Contagion in New Product Diffusion
Racial Homophily and Its Persistence in Newcomers' Social Networks
Latent Space Approaches to Social Network Analysis
What Would It Take to Change an Inference? Using Rubin’s Causal Model to Interpret the Robustness of Causal Inferences
The Collective Dynamics of Smoking in a Large Social Network
The structure of scientific collaboration networks
The Spread of Obesity in a Large Social Network over 32 Years
The central role of the propensity score in observational studies for causal effects
Community structure in social and biological networks
Emergence of Scaling in Random Networks
Identification of Endogenous Social Effects
Policy Interventions, Low-Level Equilibria, and Social Interactions
Recent Developments in Network Measurement
Social Networks and Causal Inference
Behavior in Public Places
The Small World of the American Corporate Elite, 1982-2001
A Latent Space Network Model for Social Influence
Effects of missing data in social networks
Longitudinal analysis of friendship networks
Detecting measurement bias in respondent reports of personal networks
Models of core/periphery structures
An introduction to exponential random graph (p*) models for social networks
Question-order effects in social network name generators
Missing data in networks
Alternative estimation methods for identifying contagion effects in dynamic social networks
QAP partialling as a test of spuriousness
Seeing things clearly
Modeling social influence through network autocorrelation
The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis
Using Social Network Analysis to Study How Collegial Interactions Can Augment Teacher Learning from External Professional Development
Insiders' Perspectives on Reasons for Attraction to a Close Other
Impact of a Confounding Variable on a Regression Coefficient
Instrumental variables estimates of peer effects in social networks
Toward a more complete understanding of the reciprocity of liking effect
A Set of Measures of Centrality Based on Betweenness
Dynamic models of segregation
The Effect of Perceived Liking on Interpersonal Attraction
The prediction of interpersonal attraction
Dynamic Networks and Behavior
Indices of Robustness for Sample Representation
Social influence and opinions
Influence of measurement errors on networks
Kinds of Third-Party Effects on Trust
Interaction Preludes to Role Setting
Network influences on policy implementation
Beyond Individual Differences
The Structure of a Social Science Collaboration Network
Structuralism versus Individualism
Informant Accuracy in Social Network Data
Cognitive Structure and Informant Accuracy
Network Studies of Social Influence
Sensitivity Analysis for Contagion Effects in Social Networks
Homophily and Contagion Are Generically Confounded in Observational Social Network Studies
Causality in Social Network Analysis
Focus, Fiddle, and Friends
Social Capital and the Diffusion of Innovations Within Organizations
Dynamics of Dyads in Social Networks
Birds of a Feather
Network Data and Measurement
Informant Accuracy in Social Network Data Ii
Origins of Homophily in an Evolving Social Network
Collaboration and Creativity
Network Analysis, Culture, and the Problem of Agency
The Focused Organization of Social Ties
Homophily, Selection, and Socialization in Adolescent Friendships
The Strength of Weak Ties
Networks, Dynamics, and the Small-World Phenomenon
Informant accuracy in social-network data V. An experimental attempt to predict actual communication from recall data
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |