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This chapter is devoted to understanding how the main ideas in graph theory and combinatorics optimization can assist insight-driven problem solving, and thereby, create public impact. The reader sees how such ideas have laid the foundation for apps such as Google Maps and how they are being used to improve our understanding of social networks, design transportation networks, create efficiency schedules for sports events, enhance cryptosystems, and improve the efficiency of supply chains. The reader also learns how analytics scientists have been able to learn from the amazing ability of nature in problem solving (swarm intelligence) and use this to develop effective insight-driven problem solving approaches that can yield powerful insights in addressing complex societal problems.
Debates about the nature of a deepening educational divide in politics tend to focus on education as an individual-level characteristic, whether as a marker of skill endowment, an experience instilling certain values, or the consequence of self-selection based on earlier socialization. We instead look at how education (both level and field) relates to political outcome variables as a feature of social networks. We take cleavage-theoretical perspectives on the educational divide one step further by treating individuals not as atomistic entities but as embedded in social structure. Using original surveys from Germany, the UK, and Switzerland, we show that educational divides are diminished in the presence of countervailing networks. Looking at vote preference and indicators of social closure like group identity, this study suggests that segregated social networks contribute to stabilizing contemporary cleavage structures, even as the mass social and political organizations that shaped twentieth century cleavage politics have declined.
English historical sociolinguistics traces the transition of a ‘small’ language into a ‘big’ one. Old English was a small language in terms of its regional coverage and number of speakers, whereas Present-day English is a comprehensively documented world language with hundreds of millions of first-language speakers. Its 1500-year history involves gradually developing social structures of different timescales, but it was also affected by abrupt changes brought about by forces such as invasions and pandemics. Sociolinguistics highlights the agency of language users in shaping and changing their language and, consequently, the society they live in. Written records on individual language use are sparse from the earliest periods but multiply as people from different walks of life become literate and pass on data on their linguistic practices. With time, increasing efforts are, however, also expended on regulating usage with the aim of language standardisation.
Palmyra is usually studied for one of three reasons, either its role in the long-distance trade between Indian Ocean and Mediterranean, its distinctive cultural identity as visible in the epigraphic and material record from the city or its rise as an independent regional power in the Near East in the third quarter of the third century AD. While Palmyra was indeed a special place, with a private sorte, or destiny of its own, as Pliny famously expressed it (HN 5.88), the city’s ability to maintain its distinctiveness arguably rested on deep entanglements with her local and regional surroundings. This chapter addresses how the city engaged with its neighbours and its Roman imperial overlords. Actions, events and policies attested in the epigraphic record from the city and from the Palmyrene diaspora in the Roman Empire are discussed in light of theoretical insights from archaeology, sociology and economics. It is argued that Palmyra’s remarkable success built on the city’s ability to connect with the range of social networks that constituted the Roman Empire.
This chapter explores the concept of networks, discussing their relationship to intergroup relations, system stability, and system change. It reviews emerging research that connects group processes with social network analysis, particularly in the context of attitudes and ideological polarisation. Concepts such as nodes and edges are discussed in relation to how systems can be represented, and theories of influence and change. Drawing from the literature on system stability, we discuss the concepts of homeostatic mechanisms (mechanisms that seek to preserve stability) and resilience (the preservation of systems in the face of disruptions), and link these to the literatures in Part 1 on identities, groups, social influence, and collective actions.
This study expands theoretical research on negotiated culture by testing basic assumptions in the context of a German–Japanese joint venture. Data collected by semi-structured interviews are analyzed using textual analysis software to uncover key issues that became catalysts for negotiation. Results include a model of cultural negotiation linking organizational events with issue domains as points of departure for negotiations. Results show that aggregate models of cultural difference are useful only to the extent that they serve as latent conceptual anchors guiding individuals’ cultural responses to events. The study shows that structural/contextual influences together with individuals’ culturally determined sensemaking with regard to specific organizational events are more useful determinants of negotiated outcomes. Authors conclude that, while it is unlikely that we can predict organizational culture formation in complex cultural organizations, we can understand the process of cultural negotiation and as a result be better prepared to monitor and manage in culturally diverse settings.
In The Autocratic Voter, Natalie Wenzell Letsa explores the motivations behind why citizens in electoral autocracies choose to participate in politics and support political parties. With electoral autocracies becoming the most common type of regime in the modern world, Letsa challenges the dominant materialist framework for understanding political behavior and presents an alternative view of partisanship as a social identity. Her book argues that despite the irrationality and obstacles to participating in autocratic politics, people are socialized into becoming partisans by their partisan friends and family. This socialization process has a cascading effect that can either facilitate support for regime change and democracy or sustain the status quo. By delving into the social identity of partisanship, The Autocratic Voter offers a new perspective on political behavior in electoral autocracies that has the potential to shape the future of these regimes.
Chapter 7 tests the four mechanisms of socialization derived from the qualitative data formally with original survey data from Cameroon. The analysis shows that, first, people raised in partisan households are much more likely to adopt partisan identities later in life than people raised in apolitical households. Second, party militants are more politically influential in their social networks than regular partisans or nonpartisans. Third, the partisan homogeneity of contemporary social networks is highly predictive of individual partisanship. Finally, because of the nature of politics in electoral autocracies, opposition partisans face higher levels of cross-partisan influence than ruling party partisans.
Chapter 6 continues to explore the qualitative data presented in Chapter 5 by presenting the full social networks of the twelve research subjects, and therefore contemporary process of socialization. The social networks produce three key observations. First, party brokers or activists play an outsized role on the socialization process within social networks. Second, for partisans of all stripes, their larger social networks tended to be much more politically heterogenous than their smaller “inner circles.” Finally, the twelve networks suggest that ruling party partisans are more politically insulated than are opposition partisans.
This article introduces item response models for rating relational data. The relational data are obtained via ratings of senders and receivers in a directed network. The proposed models allow comparisons of senders and receivers on a one-dimensional latent scale while accounting for unobserved homophilic relationships. We show that the approach effectively captures reciprocity and clustering phenomena in the relational data. We estimate model parameters using a Bayesian specification and utilize Markov Chain Monte Carlo methods to approximate the full conditional posterior distributions. Simulation studies demonstrate that model parameters can be recovered satisfactorily even when the dimensionality of the network is small. We also present an extensive empirical application to illustrate the usefulness of the proposed models for complete and incomplete networks.
Coalescing developments in brain, mind, and body bring about qualitative changes in all aspects of the teenager’s life, with both great advantages and challenges. Being able to imagine how things could be, and seeing multiple possibilities, can lead to idealism or cynicism. Teens are aware of the complexity of thought and feeling and know that neither they nor others are always aware of motives. Along with a profound sense of uniqueness, they have the capacity to connect with others in a deeper, more intimate way and to be involved in a complex network of relationships. At the same time, they can feel alone in dealing with emotions at a new level of complexity. To thrive during this period they must be able to tolerate a level of vulnerability never before experienced, because they know others may be thinking about them and seeing beneath the surface of their behavior, just as they can.
Stochastic actor-oriented models (SAOMs) were designed in the social network setting to capture network dynamics representing a variety of influences on network change. The standard framework assumes the observed networks are free of false positive and false negative edges, which may be an unrealistic assumption. We propose a hidden Markov model (HMM) extension to these models, consisting of two components: 1) a latent model, which assumes that the unobserved, true networks evolve according to a Markov process as they do in the SAOM framework; and 2) a measurement model, which describes the conditional distribution of the observed networks given the true networks. An expectation-maximization algorithm is developed for parameter estimation. We address the computational challenge posed by a massive discrete state space, of a size exponentially increasing in the number of vertices, through the use of the missing information principle and particle filtering. We present results from a simulation study, demonstrating our approach offers improvement in accuracy of estimation, in contrast to the standard SAOM, when the underlying networks are observed with noise. We apply our method to functional brain networks inferred from electroencephalogram data, revealing larger effect sizes when compared to the naive approach of fitting the standard SAOM.
In this chapter we trace the development of the field from its beginnings to the present. Before the start of sociolinguistics proper in the early 1960s, regional dialectologists had already made considerable efforts to explore the spatial dimension of language variation, using different methodologies to collect data on regional dialects. The impact of the so-called sociolinguistic turn is discussed with reference to Labov’s early work (on the island of Martha’s Vineyard and in New York City), and some principal findings and methods of early work in the field are introduced. We will take a first look at the subsequent waves of variationist sociolinguistics, social network theory and communities of practice, which entail a focus on individual speakers and their social grouping and ordering as well as their orientation and affiliation with other speakers in indexical relationships. The chapter concludes with some recent developments and a presentation of current research themes.
This chapter highlights a diversity of women’s roles during the Revolution of Dignity, which aligns well with a hybrid model of women’s participation in a contemporary revolution. Drawing on rich data from oral history projects, the book identifies twelve main domains of women’s activism, including art production, crowdsourcing, food provision, legal aid, medical services, public order, and public relations. This chapter challenges a binary construction of women’s involvement in stereotypically feminine or stereotypically masculine activities during a period of mass mobilization. The patriarchal model of women’s participation in a revolution assumes a gender-based division of labor within a revolutionary movement, which reinforces preexisting patriarchal norms in society. The emancipatory model, on the contrary, assumes women’s access to formal positions of leadership within the movement. Located between these two extremes, the hybrid model of women’s participation in a revolution acknowledges the diversity and fluidity of women’s roles. According to the hybrid model, women might adopt three different strategies: (1) acquiescence to a traditional gender-based division of labor, (2) appropriation of the masculine forms of resistance, and (3) adoption of gender-neutral roles or switching from stereotypically feminine to stereotypically masculine roles.
Social scientists have long been interested in elite cohesion in American society, recognizing its potential implications for democracy and governance. While empirical research has focused on corporate elites and, in particular, on cohesion derived from shared board memberships, cohesion among those in the highest positions in the American state and historical change in that cohesion have been little studied. Drawing on a novel dataset of the career histories of 2,221 people who were appointed to these elite positions between 1898 and 1998, I examine whether administrative elites, prior to their elite appointment, attended the same educational institutions or worked in the same agencies of the federal government at the same time. I find evidence of increasing elite cohesion during the twentieth century. Educational cohesion increases significantly in the three decades following the World War II and then declines slightly toward the end of the century. This increase goes hand in hand with a change from college to graduate education as the primary site generating educational cohesion. Federal government workplace cohesion increases markedly in the 1930s and 1940s and then remains high. As people are appointed to different organizations within the American state, their educational and workplace connections create inter-agency networks that, it is expected, facilitate mutual understanding and coordination and thus help integrate the American administrative state.
This chapter explains different ways of studying social networks in Ottoman history. The first vein of research mainly maps social networks in different areas of the Ottoman state and society such as transportation and communication, migration, credit and finance. In the second vein of research, the emphasis is on developing a network approach and methodology based on a relational approach. The chapter provides examples of literature in both types of research in Ottoman history. It introduces some social network concepts such as structural holes, bridge, and brokerage. It also discusses the advantages and disadvantages of using qualitative and quantitative network analysis in historical research.
We investigate how the selection process of a leader affects team performance with respect to social learning. We use a laboratory experiment in which an incentivized guessing task is repeated in a star network with the leader at the center. Leader selection is either based on competence, on self-confidence, or made at random. In our setting, teams with random leaders do not underperform. They even outperform teams with leaders selected on self-confidence. Hence, self-confidence can be a dangerous proxy for competence of a leader. We show that it is the declaration of the selection procedure which makes non-random leaders overly influential. To investigate the opinion dynamics, we set up a horse race between several rational and naïve models of social learning. The prevalent conservatism in updating, together with the strong influence of the team leader, imply an information loss since the other team members’ knowledge is not sufficiently integrated.
Several studies have shown a relationship between the stocks of migrants and country-level investment in the home country; however the mechanism through which this relationship operates is still unexplored. We use a field experiment in which participants who are recent immigrants send information about risky decisions to others in their social network in their home country. The results demonstrate how this information influences decisions in the home country. We find that the advice given by family members and decisions made by friends significantly affects an individual’s risky decision-making.
This paper studies the effect of social relations on convergence to the efficient equilibrium in 2 × 2 coordination games from an experimental perspective. We employ a 2 × 2 factorial design in which we explore two different games with asymmetric payoffs and two matching protocols: “friends” versus “strangers”. In the first game, payoffs by the worse-off player are the same in the two equilibria, whereas in the second game, this player will receive lower payoffs in the efficient equilibrium. Surprisingly, the results show that “strangers” coordinate more frequently in the efficient equilibrium than “friends” in both games. Network measures such as in-degree, out-degree and betweenness are all positively correlated with playing the strategy which leads to the efficient outcome but clustering is not. In addition, ‘envy’ explains no convergence to the efficient outcome.