Public policy-making provides fertile ground for exploring the power of actors and coalitions in coordinating governance networks through the management of ideational conflicts and control over resource flow (Sabatier, 1988; Ingold, 2014). Our research looks at the structural and cognitive conditions that make it possible to identify key actors in policy processes using a significant case study: the Direction Nationale de la Planification et de la Gestion des Crises Alimentaires (DNPGCA) in Niger. This multi-actor system aims to implement the country's food, nutrition and pastoral security strategy program. The network under study brings together about fifty actors, such as international donors and NGOs, government bodies, civil society actors and private sector, whose objectives may differ, making it an ideal field of study for analysing the policy process, considering power relationships. Our analysis mobilises sociometric data on the relationships and resources exchanged in the governance network and information on the policy beliefs held by actors. Using these data, we propose to analyse the influence of policy brokers by looking at the articulation between these two worlds (resources and ideas) interacting through the actors. Drawing on the work of the Advocacy Coalition Framework and Resource Dependence Theory, we propose the hypothesis that a policy broker is all the more relevant if he occupies a position of intermediary in the resource network but that he is also a broker of ideas capable of promoting compromise between conflicting coalitions. Through this demonstration, we argue that the power of the policy broker can only be assessed with regard to these two interconnected levels.

Social movements rely on orgnizational coalitions to help mobilize large numbers of people. Yet, power imbalance within coalitions can affect the success of movemnet. While larger organizations provide essential resources—such as funding, visibility, and political connections—that enhance a coalition’s capacity, this concentration of power can create challenges. Smaller organizations may become dependent on these resources, limiting their autonomy and influence. Additionally, larger organizations often prioritize their own strategic objectives, which may not align with the missions of smaller groups.

This study explores how power imbalances between larger and smaller organizations shape coalition stability and movement outcomes. It argues that while such coalition structures can facilitate movement formation by providing essential support at the intial stage, they may also introduce tensions over time. As these imbalances persist, they can lead to conflicts that weaken coalition cohesion and, in extreme cases, contribute to its dissolution.

To examine these dynamics, this study draw data from the Dynamics of Collective Action (DOCA) dataset to map event-based coalitions in the U.S. from the 1960s to the 1990s. By analyzing how power asymmetries influence coalition stability, this study sheds light on the internal dynamics of social movements and the role of coalition structure in shaping movement success and long-term viability.

Protests are the most common means of activism. Whether in a public (demonstration) or private (strike) context, it is seen as one of the most widespread methods of expressing disagreement in social, political and environmental contexts. When people protest, they may go to great lengths to organise actions that involve significant time, material and ultimately economic costs for the organisers. But what about the impact? Whether it is civil disobedience or the most typical and classic demonstrations, we all know the media impact of these actions. The psychological impact is even studied. But what about the material impact on the infrastructures themselves ?

This is what we aim for, and we do it using real data and tools from network science.

To this end, we introduce link stream differentiation using link streams, a model for temporal graphs. Inspired by classical differentiation and combined with a clustering method to highlight the most disrupted connected component, it allows us to analyse the temporal and structural extent of disruptions in real networks as well as their return to equilibrium.

We apply this method to analyse the ILWU dockworkers' strike in the US West Coast ports in 2002 and the social unrest related to the pension reform in France in 2003, in order to gain deeper insights into these events and their impact on the network. We use data on the maritime trade network from Lloyd's List and data on traffic on the Paris road network from OpenDataParis.

Civil society organizations (CSOs) play a crucial role in providing services, advocating for social causes, and represent diverse interests. These organizations are also ‘adversarial’ vis-a-vis government as they often deal with issues that are politically difficult, such as supporting migrants. While their role in providing social services - often compensating for the lack of public offer - has been examined in depth in the literature, there is a shortage of studies investigating how CSOs develop local strategies based on networking for achieving their targets.

To address the above research gaps, this work explores the strategic behaviour of CSOs in supporting migrants in Milan’s San Siro district - in response to public agencies’ failure to provide adequate social support. Indeed, these organizations often operate with limited resources, prompting the need for strategic collaborations and innovative solutions via informal channels.

Using a mixed-method approach, we combine social network analysis and content analysis - using primary data from interviews and questionnaires - to investigate actors’ relational patterns. Our findings from the exponential random graph models and the themes detected in the interviews highlight both strengths and limitations of the informal networking system developed by CSOs. Local organizations tend to diversify their offer by relying on diverse actors, but they also show similar strategies when it comes to reaching their targets. These findings underscore the need for institutional recognition, sustainable funding mechanisms, and policy frameworks that enhance collaboration between formal and informal actors.

When we settle in for a nice cup of coffee, or enjoy a rich piece of chocolate, the environmental impacts of producing those items often don’t cross our minds. However, deforestation and habitat loss, not to mention social injustices, continue to plague food supply chains, particularly when they involve international trade. In response, countries are increasingly enacting legislation to curb the environmental and social harms tied to food commodity supply chains. But the policy process is complicated by multiple and competing interests that impede the progress of corporate accountability policy instruments. To better understand the landscape of influence in these policy actor networks, we examine the case of emerging supply chain due diligence legislation in Canada. While some headway has been made to stymie forced labour in supply chains through the passage of Canada’s Modern Slavery Act, efforts to address environmental impacts of global supply chains appear to have stalled. This raises important questions about which actors hold influence in the initiation and development of due diligence policy in Canada, and whether certain interests have been marginalized. As part of an iterative consultation process, we ask organisational representatives about their involvement in the policy process and their interactions with others in relation to due diligence. We measure degree, betweenness, and eigenvector centrality to assess direct influence, reach, and strategic connection within the network. Understanding this network of influence can not only help diagnose barriers to establishing due diligence policy, but can also lay the foundation for dialogue that could lead to consensus around a path forward.

Instant Messaging (IM) services have become crucial for Social Movement Organizations (SMOs), enabling activist coordination, information distribution, and mobilization for protest events. While previous research highlights the reduced importance of local dependencies due to digital communication, many left-wing SMOs continue to rely on decentralized local action as a core organizational principle. Antifa exemplifies this dual structure, leveraging Internet Communication Technologies (ICTs) and instant messaging to combine localized direct action with an (inter)national activist network. Existing case studies suggest that local demonstrations remain vital for antifascist groups in European cities. However, the role of spatial proximity in information diffusion and mobilization within these networks remains understudied. This study examines how spatial proximity influences information dissemination among German antifascist groups and channels on Telegram over time, considering their strong reliance on IM services and localized offline protest behavior. Using transportation time by car and bus as a proxy for spatial proximity, we analyze event-driven communication patterns. We extract topics from (forwarded) messages and mentions in German antifascist Telegram groups and channels linked to direct actions, constructing a longitudinal network dataset to track information diffusion over time. Stochastic Actor-Oriented Models (SAOMs) assess how transportation time affects information diffusion dynamics. Additionally, we test the role of ideological and topical similarity in shaping dissemination patterns. By integrating natural language processing and network analysis, this study provides empirical insights into the structuring impact of spatial proximity on mobilization in a fragmented yet interconnected digital antifascist landscape.