Conference Agenda

This paper advocates thinking of political capital within a social network ecological framework and suggests that although network position forms the structural basis for individual levels of political capital, the political environment within a given political ecosystem determines how and when social ties are put into action. The political network changes little in the short run, but the costs and benefits of political action will influence perceived tie strength and political obligation depending on the political environment (e.g., the political environment created by 9/11). In viewing political capital in such a manner, we engage in an empirical examination of these ideas through the study of a policy network in North Carolina over a 6-year period, examining individual variation in reputed political influence as it relates to various kinds of network centrality, structural holes, cognitive knowledge of the network, and political outcomes at three points in time. At a macro level we examine individual variation in reputed political influence as it relates to various kinds of network centrality, structural holes, cognitive knowledge of the network, and political status at three points in time. Included are legislators, lobbyists, state government officials, and activists involved in passing a piece of environmental legislation. At the micro level, we examine the political capital over time for two political antagonists (lobbyists representing opposing industries), examining how the development of and change in such capital is related to political outcomes.

This paper introduces a novel field for applying network analysis to political phenomena by conceptualizing transitions in discrete political state spaces as transition networks. By examining transitions in key areas—political regimes, institutional governance structures, and policy regimes—this approach aims to categorize transition paths and identify structural similarities, thereby enhancing our understanding of political development patterns. Larger datasets allow for analysis using relational event models.

First, the paper explores regime transitions in ancient Greece, tracing shifts between democracies, autocracies, and hybrid regimes. By constructing a network of regime types and their transitions, it identifies patterns of political change, including factors that facilitate or hinder transitions. This framework provides insights into regime stability and temporal dynamics of regime evolution, with implications for contemporary democratization and autocratization processes.

Second, the paper examines transitions in institutional governance structures, focusing on infrastructure systems. It analyzes shifts between private markets, state hierarchies, and hybrid systems, highlighting mechanisms driving governance adaptation, convergence, and persistence. Institutional path dependencies and external shocks play a key role in shaping these transformations.

Third, policy regime transitions are analyzed through climate policy, tracing changes in policy instrument configurations over time. By mapping policy trajectories, this approach identifies critical junctures and dominant pathways, offering insights into how policy repertoires adapt to political and economic shifts.

By applying network analysis to political state spaces, this paper advances a relational perspective on political change and transformation, contributing to a deeper understanding of political development dynamics.

States use sanctions as a means to penalize or influence behavior in their counterparts. Sanctioned states may respond to these material penalties in different ways. On one hand, they might signal conciliatory attitudes to reduce the impact of sanctions. On the other hand, they might demonstrate resolve and willingness to absorb costs to resist external pressure. This paper uses relational event models and language measures to analyze how sanctioned states communicate their responses after being subjected to sanctions, and the network dynamics that govern sanction allocation and response.

The study of social-ecological systems and social-ecological networks allows for the joint analysis of both social and ecological systems. Managing and governing – and even more so achieving social-ecologial fit in – social-ecological systems has been claimed to be complex, because of actors’ lack of knowledge about the complex ecological interdependencies, but also because of the dynamic nature of ecological interdependencies. This paper addresses the question of how actors in a social-ecological system address potentially changing ecological systems and related interdependencies. More specifically, we study a river basin in Switzerland and rely on survey data on actors involved in managing the river basin. We further rely on ecological data about connectedness of river patches, and how this connectedness might change depending on a) climate-change induced future scenarios, and b) the addition or removal of man-made barriers and the improvement or deterioration of water quality. This allows us to work with different scenarios of ecological interdependencies, and assess to what degree actors are able to consider these scenario-based interdependencies into their network structure, and where there might be gaps in the collaborative actor network to address future scenarios. We rely on ERGM analyses of the social-ecological network.

The undertaking of several studies of political phenomena in social media mandates the operationalization of the notion of political stance of users and contents involved. Relevant examples include the study of segregation and polarization online, or the study of political diversity in content diets in social media. While many research designs rely on operationalizations best suited for the US setting, few allow addressing more general design, in which users and content might take stances on multiple ideology and issue dimensions, going beyond traditional Liberal-Conservative or Left-Right scales. To advance the study of more general online ecosystems, we present a dataset of X/Twitter population of users in the French political Twittersphere and web domains embedded in a political space spanned by dimensions measuring attitudes towards immigration, the EU, liberal values, elites and institutions, nationalism and the environment. Positions are derived using a method for ideal point estimation on a bipartite network between members of parliament and their followers. We provide several benchmarks validating the positions of these entities (based on both, LLM and human annotations), as well as a discussion of the case studies in which they can be used, including, e.g., AI explainability, political polarization and segregation, and media diets.