Multiplex networks and interest group influence reputation: An exponential random graph model

Interest groups struggle to build reputations as influential actors in the policy process and to discern the influence exercised by others. This study conceptualizes influence reputation as a relational variable that varies locally throughout a network. Drawing upon interviews with 168 interest group representatives in the United States health policy domain, this research examines the effects of multiplex networks of communication, coalitions, and issues on influence reputation. Using an exponential random graph model (ERGM), the analysis demonstrates that multiple roles of confidant, collaborator, and issue advocate affect how group representatives understand the influence of those with whom they are tied, after accounting for homophily among interest groups.

► Interest group influence reputations vary locally in multiplex networks.
► Gossip plays a key role in reducing uncertainty about influence reputation.
► Communication, coalitions, and issue networks matter for influence reputation.
► Groups play multiple roles of confidants, collaborators, and issue advocates.
► Communication networks an especially strong predictor of influence reputation.