arXiv subjects

Philip Leifeld

Publications and source records attributed to Philip Leifeld.

3 recordsLinked to original sources

arXiv2024

Endogenous Coalition Formation in Policy Debates

Political actors form coalitions around their joint normative beliefs in order to influence the policy process on contentious issues such as climate change or population ageing. Policy process theory maintains that learning within and across coalitions is a central predictor of coalition formation and policy change but has yet to explain how policy learning works. The present article explains the formation and maintenance of coalitions by focusing on the ways actors adopt policy beliefs from other actors in policy debates. A policy debate is a complex social system in which temporal network dependence guides how actors contribute ideological statements to the debate. Belief adoption matters in three complementary ways: bonding, which exploits cues within coalitions; bridging, which explores new beliefs outside one's perimeter in the debate; and repulsion, which reinforces polarization between coalitions and cements their belief systems. We formalize this theory of endogenous coalition formation in policy debates and test it on a micro-level empirical dataset using statistical network analysis and event history analysis.

cs.SI↗

arXiv2023

Bayesian Testing of Scientific Expectations Under Exponential Random Graph Models

The exponential random graph (ERGM) model is a commonly used statistical framework for studying the determinants of tie formations from social network data. To test scientific theories under the ERGM framework, statistical inferential techniques are generally used based on traditional significance testing using p-values. This methodology has certain limitations, however, such as its inconsistent behavior when the null hypothesis is true, its inability to quantify evidence in favor of a null hypothesis, and its inability to test multiple hypotheses with competing equality and/or order constraints on the parameters of interest in a direct manner. To tackle these shortcomings, this paper presents Bayes factors and posterior probabilities for testing scientific expectations under a Bayesian framework. The methodology is implemented in the R package 'BFpack'. The applicability of the methodology is illustrated using empirical collaboration networks and policy networks.

stat.ME↗

arXiv2018

A Theoretical and Empirical Comparison of the Temporal Exponential Random Graph Model and the Stochastic Actor-Oriented Model

The temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several theoretical differences the analyst might consider and find that with some specifications, the two models behave very similarly, while each model out-predicts the other one the more the specific assumptions of the respective model are met.

stat.ME↗