Evaluating Methods for Estimating Influence Effects in Social Networks: A Simulation Study

Thomas M. Menino Convention & Exhibition Center 

The contagion effect, also known as the peer effect, plays a significant role in social net-
works. It refers to the phenomenon in which one person or group can influence the behavior
of other individuals with whom they share social connections. However, accurately estimating
the contagion effect is challenging due to the confounding impact of peer selection. Previous
studies have shown that this can be viewed as a problem of omitted variable bias. In an attempt
to address this issue, simulation studies were conducted to compare the effectiveness of various
methodologies in estimating peer influence within social networks, including latent variable
models and machine learning techniques. Our research demonstrates that the performance
of various approaches vary depending on the social network scenario. Overall, the latent
space approach exhibits the best performance. This analysis provides valuable insights for re-
searchers studying estimation techniques and emphasizes the importance of understanding the
strengths, limitations, and objectives of these methods before using them for inference-based
estimation.

Contagious effect

Latent factor

Latent space

Node2Vec

SDNE 

Social Statistics Section