We investigate graph neural networks on graphs with heterophily. Some existing methods
amplify a node's neighborhood with multi-hop neighbors to include more nodes with …

Network concepts are central to at least three challenges of interest in the sustainability
science literature: how to link knowledge with action, how to enhance collective action, and …

Graph neural networks (GNNs) have shown great prowess in learning representations
suitable for numerous graph-based machine learning tasks. When applied to semi …

I nstitutional collective action (ICA) dilemmas arise from the division or partitioning of
authority in which decisions by one government in one or more specific functional area …

The development of stochastic models for the analysis of social networks is an important
growth area in contemporary statistics. The last few decades have witnessed the rapid …

The Institutional Collective Action (ICA) framework has contributed to understanding
collective action problems in fragmented governance and identified mechanisms for …

How do social networks differ between highly collaborative and less collaborative forms of
governance? Drawing on a prior study that characterized the level of collaboration for three …

Social-ecological systems are governed by a complex of ecology of games featuring
multiple actors, policy institutions, and issues, and not just single institutions operating in …

The study of public policy deals with subsystems in which actors cooperate or compete to
turn their beliefs into policy solutions. Yet, most studies concern mature subsystems in which …

When rebels make alliances, what informs their choice of allies? Civil wars are rarely simple
contests between rebels and incumbent regimes. Rather, rival militant networks provide the …