A valuable feature of networks is their ability to quantify structural relationships. Much like a chemist who, having purified their sample, can bring to bear a wide range of tools for understanding their sample by transforming data into a network, a network scientist can leverage a range of tools that provide precise measurements of their data’s structure. This includes node-level measures like degree and centrality, meso-scale measures like community formation, and macro-scale measures like density and modularity. This chapter introduces these measures and gives a brief guide to their use.

This chapter introduces some technical details about networks. Although they may seem like a complication that could be saved for later, the details presented here are actually a useful starting point. They will provide a sense of the many options for ways that a network can matter, which is helpful to have in mind when constructing a theory that will guide data collection. A social network is a record of a set of relationships – links – among actors in a group of interest. Depending on which relationships are present, an individual may find herself in a very different network position than someone else. Different groups can have different patterns of relationships, which means there can also be variation across networks. This chapter will help us be precise in these comparisons across actors and across networks and will highlight why they can be relevant to empirical research.

Chapter 6 illustrates that household political cooperation begets a system of political organization that centers on men. Using network data from a census survey, it describes the structure of the overall village political network, including gender homophily of political ties, centrality in the entire network, and the average degree of connectivity between individuals and political elites. It shows that village political networks are structured such that men comprise the center of the network, while women remain on the periphery. As a result, influence is concentrated among men, and village politics is structured around men’s other intersecting identities, namely caste. It then compares the size and composition of women’s and men’s political networks and show that women are connected to village politics largely through the men in their household. For men, women do not register as political actors. Household political cooperation thus implies strong limits on women’s access to power, influence, and information and yields a broader gender and political system that perpetuates male dominance.

Some people take orders all day. Others give them. And most people are somewhere in the middle. While relations of “who orders whom” are generally established through formalized hierarchies of authority, informal relations such as business partnerships and even friendships are also frequently hierarchical in some way: some business partners have more control over important resources, some friends have more clout. Indeed, status and reputation structure almost all areas of social life. To understand social structure, we must attend to both horizontal relations in which individuals are connected through frequently mutual feelings of belonging, as well as vertical relations of power, authority, deference, and status that are asymmetric. Ultimately, how community and hierarchy combine is one of the most vexing concerns in the social sciences. Building on the previous chapter’s focus on groups and cohesion, this chapter focuses on aspects of social structures that are more asymmetric, centralized, or hierarchical.

Given China’s position in Pacific Asia, defining its regional centrality might seem a simple task. But centralities grander than merely geographical have been alleged and contested. Currently some maintain that China is the central kingdom because of its power. But it was conquered by the Mongols and the Manchus, and its present centrality is due more to its economic mass and connectivity than to its military. Others claim that hierarchy is natural to Asian culture, and China is the apex. But neighbors were often cynical about China’s moral stature, and China’s soft power is now at a low ebb. I argue that China was the center of regional attention in the premodern era, and that it has returned to center stage since 2008. The three basic reasons for China’s original centrality and its return were situational: presence, population, and production. The salience of all three disappeared with Western imperialism’s global presence, the devaluation of mere demography, and industrial production. Traditional and current centrality created asymmetric relationships between China and its neighbors, but the regional situations differ fundamentally.

No account of the ‘rise of the modern British state’ would be complete without an appreciation of the ways in which local institutions, constitutional principles and precedents, laws – and ultimately governance – evolved. Prior to the twentieth century, locality defined the overwhelming majority of British subjects’ lived constitutional experience: the shire rule of Anglo-Saxon ealdormen, medieval corporations and county corporates, fourteenth-century Quarter Sessions, the empowered Elizabethan parish, and then the explosion of ‘ratepayer democracy’ in the nineteenth century featuring municipal corporations and county councils, Poor Law unions, and ad hoc statutory bodies (including school boards, public health authorities, and improvement committees) of all kinds.

This chapter explains how we might use Social Network Analysis (SNA) in studying agreement-making in global environmental governance. It explains a number of the key methodological processes involved in doing SNA, regarding different ways to go about data collection and specific analytical techniques that can be used within SNA that are of particular interest within studies of global environmental governance, such as network structure or the brokerage position of particular individuals or organizations. It also shows how SNA has used by scholars in the field, notably to study patterns of connection within global governance complexes, forms of authority of specific groups of individuals within environmental governance, for example deriving from positions within scientific or professional networks. Finally it makes a number of suggestions about how to thinking about integrating SNA into broader mixed-method studies of agreement-making, including using it as background research prior to visiting negotiating meetings, to identify patterns to be explored in other ways at those sites, as well as to use the negotiating sites themselves to generate accounts of social networks in action in environmental governance.

Chapter 5 introduces network analysis. Social media data frequently has elements that are amenable to network analysis, including friend/follower networks and retweet networks. This chapter addresses how to collect and operationalize this data into measures appropriate for network analysis. It shows how to collect en masse the timelines of a given set of users, in addition to traversing their friend and follower networks. In addition, it demonstrates how to do so by collecting all tweets of all members of Congress in real time. Finally, it demonstrates in applied form how to identify automated accounts (bots) among the data being collected.

This chapter looks at how Asia’s connections world is configured, highlighting the extraordinarily pervasive nature of ties between business and politics and the networks on which they are based. Most of these relationships are strongly transactional but they also affect how individuals and companies organise themselves. For example, the institutional framework for private companies is often designed to leverage resources and assets, as well as gaining advantage, whether in relation to the regulator or competitors. We use a novel dataset with information on politically-exposed persons and institutions throughout Asia to map the various networks at the level of each country. There are significant differences between countries, mainly resulting from the variation in political systems. The network maps are complemented by detailed cases and examples from across Asia. Whatever the local variation, these webs of connections bind together with common purpose. Leveraging connections for mutual benefit delivers large and enduring benefits that have mostly proven resistant to changes of government or even political regime. Such behaviour also cuts across political systems.

Building on the discussion of the Belt and Road Initiative, the chapter offers a comprehensive inquiry into China’s economic statecraft. It first argues that the analogy often drawn between the BRI and the Marshall Plan misconstrues contemporary China’s economic statecraft. It then examines how the interest communities and partnership diplomacy serve as mechanisms for China’s economic influence. The next section considers how, with Chinese economic ascendancy in Asia, a semblance of Chinese centrality in Asia is emerging. The following section looks at China’s global influence effect in terms of the international discourse on its great-power standing as well as its drive for technical standard-setting in key industries. Lastly, the chapter discusses the built-in limits of the BRI and broad limitations of the Chinese economic statecraft in the twenty-first century.

This chapter extends the ideas of complex data by looking into cybersecurity through network and graph data.

The work by Elizabeth Bott is still mentioned as a "hypothesis" even though it has inspired many researchers over generations, pointing out that the subject is not closed. She raised a new fundamental question about the link between network structure and the forms of conjugality, which remains relevant in a world that has evolved in the social, cultural, and scientific domains. Networks are considered not only an object of research, rather they shed light on other objects (way of life, culture, behaviors, etc.). Today, Bott’s questioning may undergo some shifts as some social realities have changed and the lenses for observing these realities have also progressed. Advances in network analysis and in cultural and gender studies, as well as the more recent emphasis on relational dynamics, all contribute to further explore her question and give new insights on her hypothesis. The greater accuracy of the categories of both network structures (specifying the position of the partner) and conjugal roles (dividing them between norms and practices, then decisions and tasks) allows a more detailed description of their ways of combination. The dynamic dimension makes it possible to differentiate between contrasting processes of building a couple and integrating the partner into people's relational universes.

Katz and Lazarsfeld’s Personal Influence introduced the world to the impact of networks on the dissemination of mass media. Their “two-step flow” model showed that broadcast signals reached most of the public by being filtered through well-connected people – “opinion leaders” – who were the primary receivers of media messages, and the primary vehicles through which those messages were then disseminated to everyone else. Scientific and industry attention soon shifted to the task of identifying who the opinion leaders were, and how they could be targeted to spread new content. I trace these intellectual developments through to the arrival of social media, which brought greater attention to the idea of “central” players – or “influencers” – in the social network, as the key leverage points for disseminating products, ideas, and political messages. I show how this scientific search for the sources of social influence eventually led to a paradox: the unlikely finding that many social contagions do not spread from the central players to the periphery, but rather from the network periphery to the center. To explain these startling findings, the distinction between simple contagions, like information and viruses, and complex contagions, like social innovations and political movements, shows how the spread of new ideas through social networks depends in counterintuitive ways on the complexity of the contagion and the structure of the social network.