Communities and Networks

Using Social Network Analysis to Rethink Urban and Community Studies

Katherine Giuffre

• Publisher: Polity
• Year: 2013
• Print ISBN:
  9780745654201
  9780745654195
• Edition: 1
• eBook ISBN:
  9780745664613
• Topic: Social Sciences
• Subtopic: Urban Sociology
• Index: Social Sciences

In Communities and Networks, Katherine Giuffre takes the science of social network analysis and applies it to key issues of living in communities, especially in urban areas, exploring questions such as: How do communities shape our lives and identities? How do they foster either conformity or innovation? What holds communities together and what happens when they fragment or fall apart? How is community life changing in response to technological advances?

Refreshingly accessible and built on fascinating case examples, this unique book provides not only the theoretical grounding necessary to understand how and why the burgeoning area of social network analysis can be useful in studying communities, but also clear technical explanations of the tools of network analysis and how to gather and analyze real-world network data. Network analysis allows us to see community life in a new perspective, with sometimes surprising results and insights, and this book enables readers to gain a deeper understanding of social life and the relationships that build (and break) communities.

This engaging text will be an exciting new resource for upper-level undergraduate and beginning graduate students in a wide range of courses including social network analysis, community studies, urban studies, organizational studies, and quantitative methods.

1 What is network analysis
and how can it be
useful?

Humans are inherently social beings. We have lived in communities as long as we have been human. We form communities and, in many ways, communities form us. Our lives in communities shape who we are and how we approach the world. Understanding how communities work is vital to understanding our lives, but communities are complex and analyzing them can be difficult. They are spaces both of cooperation and of conflict. They can give us both a sense of belonging and one of alienation. They can root us in a place and also allow us to transcend the confines of geography.

For example, in the 1690s the Puritan village of Salem, Massachusetts, erupted in a paroxysm of witch-hunting the likes of which had never before been seen in North America. In the 1930s, community after community of solid citizens in Germany turned on their neighbors and succumbed to Nazism. What was happening at the level of the community to make the citizens of these places behave in these ways?

In the early twentieth century, Jewish immigrants from Eastern Europe to Chicago gradually assimilated into the American culture. In the late twentieth century, however, Indochinese refugees to Boston were the victims of arson by their neighbors who wanted the Indochinese out of their community. How and why do different communities react differently to the presence of outsiders in their midst?

In the 1960s, the residents of the ghetto in Washington, DC, responded to the assassination of Rev. Martin Luther King, Jr., with days of riots and looting. In the 1980s, the residents of New York City responded to the AIDS crisis by building a broad network of organizations intended to respond to a wide-ranging population of people in need. How and why does crisis elicit such different responses from different communities?

Community members can provide social support for each other in a variety of ways and that support can play a part in, for example, the explosion of innovative thinking that characterized Silicon Valley at the end of the twentieth century. But community members can also exert enormous pressure on each other to conform to established traditions, customs, and ways of thinking or risk being ostracized from the group and all of the social goods that it provides. How do members of communities navigate this tension between support and suffocation? Are there new types of communities emerging in the twenty-first century that are better able to maintain the balance between having too much community support and having too little?

These examples illustrate some of the ways in which communities are complex, many-faceted phenomena. Analyzing communities and communal life, therefore, is fascinating, but can at times seem overwhelming. Social network analysis helps make sense of all of this. Using social network analysis to look at community structures can give us a new perspective, new insights, richer understanding, and surprising answers to questions like the ones above and many more. The rise of social network analysis in the past half century has opened up wide ranges for exploring the questions of how human life is organized on a variety of levels and in a variety of disciplines. This book will look at how incorporating network analysis into urban and community studies can help us to understand questions and issues in those fields and can lead us to think about problems in new and fruitful ways.

What is structure?

Network analysis is the study of structure. But what do network analysts mean when they use the term “structure”? Berkowitz writes that “[t]he idea that social systems may be structured in various ways is not new. In fact, all of the established social sciences have evolved some notion of structure. But, until recently, no field had taken the idea of a regular, persistent pattern in the behavior of the elementary parts of a social system and used it as a central or focal concept for understanding social life” (1982: 1, emphasis in original). Wasserman and Faust add, “Regularities or patterns in interactions give rise to structures” (1994: 6–7).

What this means in the context of network analysis is that the persistent patterns of relations among the participants in a system become the core of the analysis. It is the relationships between the members of the system rather than the individual attributes of those members that are the key component of understanding the system. For example, network analysts would focus on the web of relations among various artists and galleries (rather than, say, the talent of individual artists) in order to understand why some artists find success in the art world and others do not (Giuffre 1999). The logic behind this thinking is part of our everyday understanding of how the world operates when we say things like, “It’s not what you know; it’s who you know.” Network analysts do not stop at merely “who you know,” however, but investigate much more deeply into the persistent patterns of those relationships. These patterns of relationships are what we call “structure” (Wasserman & Faust 1994: 3).

Much social science research in a variety of fields focuses exclusively on individual attributes (like talent, in the example above) and ignores important information about the patterns of relations among the members of the system (Wasserman & Faust 1994: 6–7). Network analysts, however, argue that “structural relations are often more important for understanding observed behaviors than are such attributes as age, gender, values, and ideology” (Knoke & Yang 2008: 4).

Social network analysis, then, concentrates on relations among the members of a system rather than on the individual attributes of those members. This is because patterns of relations have consequences. Again, this is the kind of everyday thinking we employ when we say that people looking for jobs should “activate their networks,” or that the “environment” in Silicon Valley is conducive to producing innovative thinking, or that the American economy suffered as the country lost its “position of dominance” in the system of global trade, or even that a friend going through a difficult time needs others to rally around with emotional support. In fact, one of the earliest examples of the type of work that we now think of as network analysis was Moreno’s 1934 study of how the “social configurations” surrounding individuals affected their psychological well-being (Moreno 1934). More generally, “[t]he central objectives of network analysis are to measure and represent these structural relations accurately, and to explain both why they occur and what are their consequences” (Knoke & Yang 2008: 4).

Because the relations among the members of a system can have profound consequences, it is important to understand how those relations fit together – how they are structured. Network analysts, therefore, gather data on the relations among the actors as their primary source of information. This relational data, Scott writes, is “the contacts, ties and connections, the group attachments and meetings, which relate one agent to another and so cannot be reduced to the properties of the individual agents themselves. Relations are not the property of agents; these relations connect pairs of agents into larger relational systems” (2000: 3).

Relational data is not about the individual members of a system (who have relations), but about relations (which occur among members of a system.) This difference may seem trivial (or even non-existent), but it is really a change in worldview, bringing the importance of the structure of relations to the fore in our understanding of how the world works. Focusing on the structure of the relations rather than on the attributes of the parties in those relations is the key to understanding network analysis. Wasserman and Faust note that “[o]f critical importance for the development of methods for social network analysis is the fact that the unit of analysis in network analysis is not the individual, but an entity consisting of a collection of individuals and the linkages among them” (1994: 4–5).

Networks as metaphors

Although the methods by which we can analyze relational data are relatively new, relational thinking has a long history in the social sciences. As far back as 1845, for example, Marx wrote in the Theses on Feuerbach: “VI: Feuerbach resolves the religious essence into the human essence. But the human essence is no abstraction inherent in each single individual. In its reality it is the ensemble of social relations” (Marx 1978 [1845]: 145). That is, Marx argues that it is our relations with others – our real, lived relations – that make us who we are.

In the early twentieth century, the work of Georg Simmel pushed the relational thinking behind network analysis to new heights. Simmel, one of the founders of the field of sociology, wrote prolifically on the relationship between individuality and social forms, especially during the transition to modern urban life. Simmel’s idea of the development of individuality (discussed in more detail in chapter 2) is based on a notion of the dynamic between social circles and individuals with each forming and being formed by the other. Simmel’s study of these social forms – which he referred to as the “geometry” of social relations – was the basis of “formal sociology.” The “forms of sociation” are made by individuals who are tied together in relations. Simmel particularly concentrates on exchange as the form of interaction through which society is formed; religion, economy, and politics, he argues, are all based on exchange. “Exchange,” he writes, “is the purest and most concentrated form of all human interactions in which serious interests are at stake” (Simmel 1971: 43). Social circles are themselves formed by these interactions – we are linked together through exchanges. We can see here the basis of the idea that networks are formed by relations between actors and that these networks have consequences. For Simmel, the creation of society itself is the result of these exchanges.

Simmel argues that exchange “lifts the individual thing and its significance for the individual man out of their singularity, not into the sphere of the abstract but into the liveliness of interaction” (1971: 69). This relational thinking, especially the primacy given to the role of exchanges between individuals, played a key role in the later development of network analysis. The “geometric” mindset brought relational thinking more clearly into focus.

But at first, Berkowitz notes, networks “were employed as little more than metaphors for the things social scientists were really trying to deal with: a friendship group was like a ‘star’ with one central point; a work group was like a small ‘pyramid’; or the spread of a rumor was like a ‘chain’” (1982: 2). While these metaphors helped social scientists conceptualize more clearly about the phenomena that they were studying, to truly be able to analyze in detail the spread of actual information through actual networks, social scientists needed more than just compelling metaphors; they needed method.

The relational thinking exemplified by Simmel was part of many disciplines in the social sciences, but it was an anthropologist, John A. Barnes, who is usually credited with first using the term “social network” in 1954 (Wasserman & Faust 1994, Knoke & Yang 2008) in his study of a Norwegian island parish. Barnes drew on Moreno’s work on “social configurations” and emotional well-being (mentioned above) and, specifically, on Moreno’s ground-breaking tool for analyzing these configurations: the sociogram (Moreno 1934). It was the advent of the sociogram that allowed network thinking to move from metaphor to method.

Metaphor into method

A sociogram¹ is a picture of a network of relations, where the members of the network are represented by points and the relations between them are represented by lines connecting the points. The map in the back of an airline’s in-flight magazine showing the airports connected by the airline’s flights is an example of a sociogram, for instance. So is the organizational chart of a company showing the chain of command in decision making or a family tree showing kinship connections. Sociograms are familiar to us now – so familiar, in fact, that it is difficult for us to conceive of the revolutionary impact that Moreno’s work had in the social sciences. “Before Moreno, people had spoken of ‘webs’ of connection, the ‘social fabric’ and, on occasion, of ‘networks’ of relations, but no one had attempted to systemize this metaphor into an analytical diagram” (Scott 2000: 9–10).

Once the analytical diagram had been developed, it was available for analysis along a number of different lines. The mathematics for the analysis came from graph theory. Graph theory is the mathematical study of graphs, which (not to be confused with bar graphs, pie charts, and other types of graphs that we think of colloquially) are simple structures consisting of a set of vertices (represented by points in a sociogram) some of which are connected by edges (the lines connecting the points in a sociogram.) Edges may have additional characteristics such as direction (going from one vertex to another and not simply connecting two vertices) or color or weight. Topological techniques in graph theory yield results about the coarse properties of graphs, such as when they are connected, have certain special paths (Eulerian or Hamiltonian, for example), or can be colored with a certain number of colors. Probabalistic, linear algebraic, discrete geometric, and other, purely numerical techniques can answer questions about densities of edges (that is, the proportion of actual ties which exist in the network) in certain graphs, the rate of propagation of some kind of signal through a graph, or of the solutions of differential equations defined on a graph, for example. Often a graph is used as a simplified version of a complex situation (such as in geometry or differential equations) where results about the graph will give approximate answers to the full, original problem. Graph theory has been extensively used in computer science to model communications networks, the connections on a single computer chip, the relationships between the components of a large software system, and so on. Graph theorists can analyze not only a sociogram, but also the translation of a sociogram into a matrix (see below). Graph theory provided the mathematical method to analyze social networks.

What is a social network?

A social network is a type of graph – a set of vertices and edges. Or, less abstractly, a social network is composed of a set of actors and the relations among them. What, then, is an “actor” and what constitutes a “relation” between actors?

“Actors” can be any social entity that is engaged in interaction with others of its type – individual persons can be actors in a network, and so can small groups like families, larger groups like civic organizations, bigger groups like corporations or even nation-states. Actors can be much more than people sharing friendships mediated through a “social networking” site like Facebook. Some examples would be workers in a tailoring shop in Zambia who attempt to organize a strike (Kapferer 1972), composers working in the Hollywood film industry (Faulkner 1987), monks forming cliques in a monastery (Sampson 1969, White et al. 1976), families vying for political dominance in Renaissance Florence (Padgett & Ansell 1993), corporations connected by shared board members (Useem 1978), public and private agencies engaged in interagency collaboration to improve school safety (Cross et al. 2009), political parties forming coalitions (Centeno 2002), or nations importing guest workers from other nations (Massey et al. 2002).

Actors are all members of the system being analyzed, but they do not necessarily all have relations with each other. Some composers working in the Hollywood film industry may work together on projects repeatedly; some may never have an...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright
• Contents
• Acknowledgments
• 1 What is network analysis and how can it be useful?
• 2 What is a community? Where does it come from?
• 3 What do communities do for us?
• 4 How do communities shape identity?
• 5 What happens when communities become fractured?
• 6 How do communities mobilize for collective action and social movements?
• 7 How do communities foster creativity and innovation?
• 8 How do new communities differ from traditional communities?
• Glossary of network terms
• References
• Index