International relations and complexity theory

Hilton Root has published some very interesting ideas about systems thinking in international relations theory in Dynamics among Nations: The Evolution of Legitimacy and Development in Modern States. Here he offers an approach to social, political, and economic change through a set of ideas that are not yet strongly integrated into IR theory — the perspective of complexity theory, worked out in a clear and useable form.

The three sources of theoretical argument which he introduces -- complexity theory, social network theory, and evolutionary ecology -- represent a significant innovation in comparative history. The novel approach Root takes consists of three large ideas: that social systems at all levels display “adaptive complexity”; that the structure of the social networks (governance systems, information systems, economic inter-dependencies) that are embedded in a specific society have important and unexpected consequences for the behavior of the system; and that complex social developments have much in common with “landscape ecology”, by which he means that there are multiple next steps that can be taken at any point leading to an improvement of performance.

His fundamental claim is that communities, states, and international systems need to be understood as dynamic systems with emergent properties. A society is not simply the linear sum of the behaviors of its component systems.

The system of international relations, like most complex ecosystems, such as the nervous system or a rain forest, is yielding to its rules of complexity. In complex systems, a central administrator rarely guides the collective behaviors that characterize development processes. The system itself has a collective behavior that depends on all its parts. Rather than convergence toward a dominant model, or “global optimum,” the interactive dynamics are coevolutionary; their interactions result in reciprocal and evolving change. (2)

One consequence of these ideas is that international relations and economic and political development processes show substantial path dependency and contingency. Another consequence is that some leading metaphors for large-scale historical change are implausible and misleading: in particular, modernization theory, “uniqueness of the West,” and “end of history.” Finally, Root argues that we should expect substantial variation in the strategies and structures that nations choose, given their own geopolitical environments.

Competition in highly interdependent global environments produces far greater local variation and diversity of structures and strategies than modernization theory ever anticipated. (3)

The book uses numerous episodes from the political, military, and economic histories of Europe and Asia to illustrate and validate the approach he takes. As a particularly interesting example of this, Root interprets Napoleon’s decision to invade Russia, not as folly, but as an intuition of the nodal character of the traditional European state system (126 ff.). He also makes repeated use of periods in Chinese imperial history to illustrate his notion that system dynamics and the structure of the governance network create very powerful obstacles to innovation and change.

So what does Root mean by “complexity”? His central concept is that of a “complex interactive adaptive system” (CIAS) within a heterogeneous environment. Here is a useful description of international relations through the lens of CIAS theory.

A network is comprised of agents. The agents interact according to shared and evolving rules of behavior that in turn define the larger environment or system. That behavior generates continuous feedback loops that enable agents to learn and to adjust their behaviors to others’ actions, thereby re-creating the system in which they operate. Complex adaptive systems are created by interactions and communications of self-adjusting agents. Continuous “feedback” motivates agents to re-evaluate their positions. Because agents are constantly reacting to other agents’ behaviors, nothing in the environment is ever fixed or finite. In order to fully understand the impacts of these agents, their behaviors must be understood as they interact with the broader system. (16)

A key analytical idea the author brings forward repeatedly is the notion of “co-evolution”. This concept captures one important aspect of a complex interactive adaptive system. CIAS’s show two types of unpredictability. First, the mutual interactions of the parts lead to “chaotic” courses of development of the system, as A, B, and C interact to produce unexpected outcome D. But second, the “adaptive” part introduces another kind of indeterminacy, as organisms, actors, and institutions change their characteristics in face of changes in the environment. So the properties of A, B, and C are not fixed over time; rather, selection and purposive adaptation lead to organisms and actors who respond differently over time to ecological opportunities and threats. 

Features of uncertainty, time framing, rule change, and novel behavior all contribute to a set of system characteristics: unpredictability, path dependency, and sensitivity to initial conditions. And Root believes that these factors have important implications about the feasibility of reducibility or micro- to macro- reconstruction:

When a state’s interactions shift from being locally based to being regionally or nationally based, its behaviors change across the network and the greater system. Thus a general theory of the system cannot be deduced from the properties of its constituent parts, just as the universe cannot be reconstructed from the fundamental laws of physics. (31)

Root's treatment of “New Institutional Economics” in Chapter 5 is important for several reasons. Most important, he demonstrates the harm that comes from incorporating a questionable theory of change into a comprehensive agenda for policy. The guiding idea of “creating institutions of good governance” as a panacea for slow economic growth and widespread poverty led policy makers to ignore other important causal factors, including locally rational but myopic strategies pursued by sub-actors. Root seems to agree with Dani Rodrik in concluding that NIC is limited when it comes to serving as a guide for positive policy design:

Assessing the legacy of new institutional economics, Harvard economist Dani Rodrik concludes that beyond “a very aggregate level of generality,” these ideas do not provide much policy guidance. (81)

Instead of looking for a general theory that can be used by centralized planning ministries to guide their economic and social policies, Root favors a more evolutionary approach: allow for a diversity of development experiments at the middle level of society, and then favor those experiments that appear to have the best results.

Chinese planners never attained the celebrity status of their Indian peers, but by trying multiple paths and starting with smaller interventions from the top, they found a better way to determine what worked. After Deng declared the opening of the Chinese economy, he instituted a multi-level process that facilitated both change and stability, and strengthened social organization and social learning through local experimentation. (108-109)

(Contrast this with the “single experiment” approach associated with land collectivization in the 1950s, resulting in massive agricultural failure and famine during the Great Leap Forward.)

Root's treatment of Imperial China’s history is intriguing but controvertible. His central premise is that China’s Imperial system was a hierarchical network of control, and systems like this are substantially less resilient and open to change than multi-nodal networks. The interpretation is reminiscent of the theory of Oriental despotism: an all-powerful imperial system suppressed both challengers and change-agents. But contemporary China historians would probably give the Imperial system more credit in terms of its degree of flexibility in face of challenges. Take peasant uprisings. The state was generally successful in its response to large peasant rebellions, even if the military response was often flat-footed. The Taiping Rebellion is an example that probably supports the author’s interpretation best, since it was local militias organized and funded by local gentry which were most successful in opposing the Taipings. But China’s history is littered with hundreds of peasant and ethnic uprisings, and its military eventually prevailed in most of them.

One way of reading Root’s book is as a guidebook for administrators in a time of complexity. Root correctly emphasizes the difficulty or impossibility of “solving” a set of social and political problems simultaneously, and the parallel difficulty of making confident predictions about medium- or long-term consequences of various policy interventions. Second best, in his account, is an evolutionary approach: try a diversity of approaches, and cautiously increase the volume of those approaches that seem to work best. But even this approach is uncertain; evolutionary processes lead to dead-ends that are unforeseen in earlier stages of the process.

(See this post about decision-making under conditions of deep uncertainty; link. And here is a series of earlier posts about social complexity; link.)

Social media and social cohesion

The current topic on the UnderstandingSociety blog poll is a proposition about social cohesion:

THE INTERNET IS HELPING TO CREATE NEW PATHWAYS OF SOCIAL COHESION IN CONTEMPORARY SOCIETY.

The poll is still open, but as of today 70% of respondents somewhat or strongly agree that the Internet creates a basis for new forms of social cohesion, while only 16% somewhat or strongly disagree. On its face, a large majority of readers are optimistic about the ability of the Internet to contribute to a stronger national community. What the poll question doesn't reveal is the respondents' underlying thinking as the basis of their judgment. So let's see what some of the considerations might be.

First, what do we mean by "social cohesion"? Along with Durkheim, we can approach the concept by relating it to the bonds of morality and loyalty that lead members of a society to adapt their behavior to the perceived needs of society. A willingness to sacrifice in times of crisis, a willingness to defer to the common good, a willingness to conform to widespread social norms -- these are the sorts of things that go into the concept of social cohesion. A society that lacks all bonds of social cohesion is one in which individuals care only about their own interests; who pay attention only to their own individual ideas about morality; and who find the idea of sacrifice for the greater good to be for the gullible. (Interestingly, this is a state of affairs that Durkheim describes as "anomie", and it is the factor that he believes conduces to a heightened rate of suicide in a population; Suicide.) (Here is a nice contemporary survey of the sociological literature on social cohesion by Noah Friedkin; link.)

Where would the social basis of this kind of cohesion come from? Ferdinand Tönnies characterizes a traditional society with a strong basis for social cohesion in terms of the idea of "gemeinschaft"; whereas he describes a modern liberal-market society in terms of the idea of gesellschaft (Community and Society: (GEMEINSCHAFT AND GESELLSCHAFT)). According to Tönnies, traditional societies maintain social cohesion through traditional social mechanisms: face-to-face relations in a village, common religious institutions, and other institutions representing and inculcating collective values. And as these traditional mechanisms have lost traction in modern civil society, the intuitive idea is that modern societies are generally declining in the level of social cohesion that they reflect.

So how might the mechanisms of social connection provided by the Internet potentially influence the facts about social cohesion in a twenty-first century society? How might Facebook, Twitter, YouTube, blogs, and webpages have effects that are either favorable or unfavorable for social cohesion? It seems that these capabilities of the Internet have the potential for working in both directions -- both undermining cohesion and enhancing cohesion. So overall, it is very difficult to assess the net impact of these capabilities.

First, consider a few tendencies in the negative direction. Much as Internet-based news sources have fragmented the audience for the network news -- and thereby have reduced the degree of commonality citizens have through their regular interactions with Walter Cronkite -- we might speculate that the Internet facilitates a fragmentation of social groups into smaller and smaller segments. So instead of a set of attitudes that bind citizens together as part of American society, we get micro-sets of attitudes that bind individuals together into micro-constituencies. This would seem to be a force working against social cohesion at the level of the population as a whole.

A related point stems from the evident ability of Internet tools to create ever-more strident groups of people around very specific issues and concerns. If each issue has its own website, Facebook page, Twitter feed, social media management strategies, and the like, individuals are drawn into greater engagement with ever-smaller groups of like-minded individuals. So it is increasingly difficult for politicians to create mass-based constituencies around a core set of values; there is a declining basis for a social consensus in a world in which individuals gravitate towards divisive social and political advocates.

These points suggest that the Internet has effects that are corrosive of social cohesion. What are the tendencies of the Internet that point in the other direction? The example of the use of Facebook during the democracy demonstrations in Egypt provides one positive indication. It would appear that activists were able to gain strong support from thousands of interested Egyptians through the real-time communication and social expression that Facebook pages enabled. This was a process of agglomeration rather than fragmentation for some period of time -- a process through which a broader and broader group of individuals became actively engaged with the values and current happenings associated with the pro-democracy movement.

Second, a little more generally, it is possible that social media like Facebook or YouTube may facilitate the development of more other-oriented interest on the part of the people who use them. If the United Way of Chicago or San Francisco can begin to attract tens of thousands of followers to a Facebook page with powerful, current information about the social needs of other Chicagoans or San Franciscans, we can imagine that there might be a rising level of willingness to get engaged in United Way fundraising and community efforts throughout the community. So YouTube and Facebook can become a contemporary alternative to the face-to-face relationships that Durkheim and Tönnies highlighted.

Third, several recent national elections have demonstrated that millions of people are willing to get involved in presidential and congressional campaigns through social media -- including the act of making online political contributions. The success of these efforts since 2006 suggests the faint possibility that online communities may begin to regain some of the pervasiveness that a fragmented television audience has lost. Perhaps this capability for aggregating large numbers of citizens around online communities of political interests suggests that the Internet can begin to help citizens build a broader consensus.

These considerations suggest that social media and the Internet have tendencies in both directions -- fragmentation and agglomeration -- with the result that its overall influence on cohesion may be neutral. In fact, we might speculate that social media enhance small group cohesion while undermining national cohesion.

In short, I'm inclined now to change my vote in the poll. I had supported the idea that the Internet is mildly favorable to increasing social cohesion. I now think that it's a wash, with negative as well as positive tendencies at work at the same time.

The math of social networks

A social network is constituted by a number of units (nodes) that are connected to each other by a defined relationship -- for example, "x cites y", "x sends 5 email messages a week to y", "x and y belong to an organization in common." There are a few wrinkles -- the units may be persons, organizations, cities, journal articles, or other types of entities; the relationships may be uni-directional or bi-directional; and the linking relationships may represent categorical relationships or intensity relationships. "x and y are friends" is a bi-directional relationship; "x and y are close friends" is a bi-directional relationship recording intensity.

Some of the basic questions about a social network are easy to formulate but difficult to assess. Basically, we would like to know what groups of individuals are unusually closely interconnected with each other, relative to the average for the population as a whole.  Here are a few basic questions that we may have about networks of people.

• Who is connected to whom? 
• Are there a subset of persons who are unusually well connected? 
• Are there sub-groupings of individuals who are more closely connected to each other than they are to others in the network? 

This last point may be put into the language of "communities": are there communities of individuals that can be identified on the basis of mathematical features of their positions within the graph of relationships defined by the data recording pairwise connections?

This question is especially important for sociologists because it goes to the heart of the reason why network maps are of sociological interest in the first place: we think that the social relationships among individuals explain important features of social action -- readiness to mobilize for a political cause, for example; this intuition derives from the idea that individuals influence each other through the exchange of information and the observation of each other's behavior; and so subgroups of persons with especially dense social connections with each other may have distinctive social characteristics as a group. So identifying the "communities" within a social network is an important sociological discovery.

This is where the mathematics of network graphs comes in. We need to have justifiable procedures for partitioning a network into sub-networks. These procedures need to make sense in terms of the intuition that there are often subgroups of nodes more closely related to each other. The procedures need to be non-arbitrary. They should be robust with respect to where we begin -- it shouldn't matter whether we begin analysis with this node or that node. And they need to be consistent with the fact that all the nodes are related to everyone else at some degree of separation. Neighborhoods that are entirely detached from the rest of the population are a trivial case; normally network ties extend transitively throughout a whole society.

Greek mathematician and social scientist Moses Boudourides is focused on this problem in his current work. (Follow him on Twitter at link.)  Boudourides is deeply sensitive to the sociological importance of the questions, so his work does a great job of bridging the two fields of thought. Some of his current work is available online, and it is very useful for people who want to understand more about the mathematics of social networks. It falls into the field of graph theory in mathematics, and it serves as a good tutorial to current thinking about the mathematics of social networks.

Worth reading first is "An Introduction to Community Detection in Graphs" (link). Here Boudourides offers a clear exposition of the mathematical problem of identifying a set of neighborhoods within a complex graph and lays out three approaches that have been taken.

Our aim here is to present an introductory and brief discussion of the formal concept of community in the context of the theory of complex networks (and social network analysis) and to describe (mostly by examples) a few of the many computational techniques which are commonly used for the detection of communities in a graph-theoretic background. (1)

Here is his definition of a community in the context of a network graph:

By a community structure of such a graph, we mean a partition of the set of nodes into a number of groups, called communities, such that all nodes belonging to any one of these groups satisfy a certain property of relative cohesiveness. Note that one may consider partitions, which are not necessarily strict, i.e., one may allow the case of overlapping communities, when there exist graph nodes belonging to more than one groups (communities) of the partition. (1)

The three iterative techniques he describes for analyzing a complex network into sub-communities are --

1. Betweenness -- Centrality-based community detection
2. k-Clique percolation
3. Modularity maximization

In each case the analysis proceeds by working through the graph iteratively, identifying notes and links with certain characteristics, and arriving at a series of stages of community definition.  This process can proceed from above (divisive) or from below (agglomerative).

The "betweenness" approach derives from an application of the idea of "betweenness centrality" of edges: "the number of shortest paths between pairs of nodes that run through that edge" (3).  On this approach, edges are ranked by their betweenness measure; the highest ranked edge is removed; and the process is repeated for the reduced graph.  This is a divisive method.

The k-clique model is an agglomerative approach, or what Boudourides refers to as a "local community-finding approach" (6).  And modularity maximization approach begins with the graph as a whole and looks for regions that are locally higher in density than the graph as a whole.  Boudourides' explanation of each of these methods is technical and clear.  He indicates that the MM approach is most widely used; but that it falls in a class of particularly intractable optimization problems like the traveling salesman problem (NP-complete).  Consequently it is necessary to design heuristic algorithms on the basis of which to arrive at approximate solutions.  (As I understand the point, however, there is no guarantee that the approximate solution will be close to the ideal solution.)

With these tools at hand, he offers a detailed example: analysis of a data set of individuals who participated in peace demonstrations against the war in Iraq and the organizations and issues with which they were associated. Data on these activists are included in the International Peace Protest Survey (IPPS).  And the resulting neighborhood maps are fascinating.  These results are described in detail in a detailed research report on "Communities in the IPPS Survey Data" [link] and a theoretical paper on "Why and How Culture Matters in Community Interorganizational Structure" [link]. These presentations show the real power of mathematical network theory, in that they bring out social relationships among individuals within this population of activists that couldn't be discovered otherwise.  Here are a pair of network graphs for 972 activists in Italy presented in "Culture Matters":

Boudourides' particular goal here is to demonstrate the difference it makes to incorporate "cultural" affiliations into the structural analysis of the first figure.  Incorporating attitudes permits simplification of the community structure of this network, from nine communities in figure 5 to four communities in figure 6.  But more generally, the analysis demonstrates the analytical gain that is possible through this analysis, allowing us to discover important patterns of affiliation among these 900+ activists.  And this, in turn, appears very relevant when we come to trying to understand their behavior within a complex process of collective action. It allows us to give some rigorous detail to the idea that a social movement has a refined micro-structure underlying its macro-level actions and demands.

What is especially useful about these papers is the help they offer us non-specialists in understanding the mathematical techniques on the basis of which we can extract sociologically meaningful information from a network graph. This is a bit analogous to the gain we get from using statistical techniques to analyze and summarize a large data set. The statistical techniques allow us to winnow the data into a few statistical measures. And the techniques of graph theory that Moses Boudourides demonstrates allow a similar analytical power for the task of making sociological sense of a large network of connected individuals. In both cases it is necessary for us to understand the basics of the mathematical techniques if we are to use the tool appropriately.

Social networks as aggregators

We think of social phenomena as "relational" in some important respect. Individuals contribute to social outcomes through structured and dynamic relationships with other individuals. So outcomes are not just heaps of aggregated individual behavior; rather, they are the filigreed result of interlinked, coordinated, competitive and sometimes unintended actions of people who have intentional and structural relationships to each other. And we think of these relationships, often, in terms of the metaphors and analytics of social "networks." So it is worthwhile giving some thought to how the machinery of social network theory can help us in better understanding the ways that social processes unfold. Here is a nice passage from Mario Diani's introduction to Social Movements and Networks: Relational Approaches to Collective Action.

It is difficult to grasp the nature of social movements. They cannot be reduced to specific insurrections or revolts, but rather resemble strings of more or less connected events, scattered across time and space; they cannot be identified with any specific organization either, rather they consist of groups of organizations, with various levels of formalization, linked in patterns of interaction which run from the fairly centralized to the totally decentralized, from the cooperative to the explicitly hostile. Persons promoting and/or supporting their actions do so not as atomized individuals, possibly with similar values or social traits, but as actors linked to each other through complex webs of exchanges, either direct or mediated. Social movements are in other words, complex and highly heterogeneous network structures. (1)

This passage emphasizes quite a few themes that have been important throughout UnderstandingSociety -- the heterogeneity of social phenomena, the difficulty of formulating a clear understanding of social ontology, and the challenge of representing the processes of aggregation through which individual social actions contribute to mid- and large-scale social outcomes.

So how do the analytical resources of network theory contribute to a better understanding of the ways that actions aggregate into outcomes?  Diani emphasizes several ways in which network analysis has contributed to the study of contentious politics. 

Network analysis as it is best known developed with reference to a 'realist' view of social structure as networks which linked together concrete actors through specific ties, identifiable and measureable through reliable empirical instruments. This view represented an alternative to both views of social structures as macro forces largely independent from the control of the specific actors associated with them ...., and views of structure as aggregates of the individual actors sharing determinate specific traits (5).

So if we take it as a plain fact about the social world that individuals have a range of meaningful and material relationships with other individuals, both proximate and distant, then it is plainly important to understand the effects that those relationships have on their consciousness and behavior.  These causal relationships are likely to extend in both directions -- from the network to the actor, and from the actor back into the network.

What kinds of social relationships are most relevant to understanding social processes like contentious movements?  Particularly important are "personal ties linking prospective participants to current activists or dense counter-cultural networks affecting rates of mobilization in specific areas" (3).  Diani mentions "personal friends, relatives, colleagues, and neighbours; ... people who share with prospective participants in some kind of collective engagement, such as previous or current participation in other movement activities, political or social organizations, and public bodies" (7).  To this list we might add membership and interaction within the kinds of civic and communal organizations that Robert Putnam emphasizes in Bowling Alone: The Collapse and Revival of American Community.

Here is the key point: different people find themselves in very different networks of social connections, and these relationships contribute to their social and political consciousness in diverse ways.  If we are interested in the spread of militant civil rights activism, as Doug McAdam is in Political Process and the Development of Black Insurgency, 1930-1970, or in the spread of fascist activism and mobilization in Europe in the 1920s and 1930s, as Michael Mann is in Fascists, it is highly relevant to discover the relationships and organizations through which individuals come into contact with each other and with the ideas of the nascent movements.  Likewise, if we are interested in the proliferation of support for the Deacons of Defense in the American South in the 1950s and 1960s, as Lance Hill is in The Deacons for Defense: Armed Resistance and the Civil Rights Movement, then it is important to identify the personal and organizational linkages through which ordinary people became aware of this response to white supremacy and violence.  Communication of ideas and political emotions requires a mechanism connecting the "signallers" and those to whom the messages eventually percolate, and this is not a depersonalized, homogeneous process.

Recruitment and mobilization is one aspect of contentious politics where social networks are plainly important.  Relationships in the workplace, the neighborhood, or the church or mosque are a likely location for the diffusion of a range of socially relevant material -- news, gossip, indignation, shared views about politics.  And these relationships are a potential vector for the recruitment of followers and activists for a range of new political ideas -- from civil rights to Tea Party to fascism.  

Identifying coalitions of collective actors is another area of current research.  Once a topic has gained some degree of visibility and salience, it is likely enough that multiple groups will begin to focus on it.  Anti-tax activism is a good example -- dozens of "citizen-based" organizations emerged in California in the 1950s and 1960s with the overall goal of limiting property and income taxes in the state, and it is useful to track the emerging relationships that developed among these organizations and their activists.

Diani also highlights the role that concrete social networks play in "framing and tactical adaptation of action repertoires" (4).  Framing has to do with the ways that issues are understood by the participants; so this topic unavoidably has to do with culture and social interpretation.  But the ways in which cultural frames are conveyed to people through a population are material processes that can be studied empirically.  And social networks play a key role in these processes.  As people interact with their friends and associates, they develop their political and social representations of the society around them.  These interactions are the direct embodiment of their social networks.  Diani singles out "communitarian and subculture networks" for particular attention: "communitarian ties operate at a minimum to strengthen the identity and solidarity among movement activists and sympathizers. At the same time, though, they provide the specific locus of social conflict in those cases where the challenge is eminently on the symbolic side and where, in other words, the definition of identities and the preservation of opportunities for the enactment of alternative lifestyles are mainly at stake" (9).  These features of identity-based mobilization, through networks of like-minded individuals, are important in Michael Mann's analysis of the rise of fascism in Fascists as well: 

The fascist core consisted everywhere of two successive generations of young men, coming of age between WorldWar I and the late 1930s. Their youth and idealism meant that fascist values were proclaimed as being distinctively “modern” and “moral.” They were especially transmitted through two institutions socializing young men: secondary and higher education, encouraging notions of moral progress, and the armed forces, encouraging militarism. Since the appeal was mainly to young men, it was also distinctly macho, encouraging an ethos of braggart, semi-disciplined violence, in peacetime encouraging militarism to mutate into paramilitarism. The character of fascism was set by young men socialized in institutions favorable to moralizing violence and eventually to murder. Yet the similarity of values between paramilitarism and militarism always gave fascism a capacity to appeal to armed forces themselves, not to the extent of inducing military rebellions but to the extent of generating sympathy there that at its most extreme could immobilize the army. (26)

“Fascists” were not fully formed at the moment they entered the movement. People may formally sign up for a movement and yet possess only a rudimentary knowledge of it – sympathy for a few slogans, respect for a charismatic F¨uhrer or Duce, or simply following friends who have joined. Most recruits joined the movement young, unmarried, unformed, with little adult civilian experience. On them, fascist parties and paramilitaries were especially powerful socialization agencies. These movements were proudly elitist and authoritarian, enshrining a pronounced hierarchy of rank and an extreme cult of the leader. Orders were to be obeyed, discipline to be imposed. Above all, they imposed a requirement of activism. Thus militants experienced intense emotional comradeship. Where the movement was proscribed, clandestinity tightened it. Many activists lost their jobs or went into prison or exile. Though this deterred many of the more fainthearted, among those remaining active such constraints further tightened the movement. (28)

The social processes that Mann describes here have to do with all three aspects -- recruitment, mobilization, and framing; and they depend on the networks of relationships through which the core fascist values and worldviews were transmitted to new recruits.  Institutions were key in this transmission -- the military, the workplace, the youth organization -- and a large part of their influence was their ability to create a significant cohort of young men with a specific set of set of social relationships.

The lens of social networks, in short, seems to be a very powerful tool for understanding the processes of aggregation -- upward, downward, and lateral -- through which ideas, grievances, and actors come together into major social upheavals and movements.

What is perhaps more difficult to see, though, is how to engage in empirical research on the concrete networks of social relationships that have important effects on outcomes we care about.  As the United States moved towards civil war in 1860 and 1861, there were hundreds or thousands of individuals in the U.S. Army officer corps who had antecedently mixed loyalties -- Southern birth, family still residing in the South, but a tradition of education and service within the U.S. Army.  So what accounts for the choices that were made by various officers when they had to decide -- North or South? It is intuitively plausible that each officer's concrete social network played an important role in his decision -- appeals from family and friends, business relationships in Virginia, long-standing relationships with senior Northern officers, an education and cohort at West Point.  But it is not entirely clear how to turn this plausible view into a feasible research plan.

This is one reason why the Diani volume is such a worthwhile contribution.  Most of the contributors focus their work on specific empirical problems in the field of social contention.  Maryjane Osa looks at activist networks in the Polish People's Republic; Christopher Ansell looks at community activism in the San Francisco Bay environmental movement; Jeff Broadbent looks at social networks in the Japanese environmental movement; and Chuck Tilly and Lesley Wood look at networks in contentious episodes in British history around 1828.  These are concrete, empirical-historical efforts to take the guiding ideas of network analysis and discover some substantive insights into the specific ways that a variety of protest movements unfolded.  And they give a better understanding of the contribution that social network analysis can offer to concrete historical research.

Trust networks

Chuck Tilly had a fascination with the mechanisms of social interaction at all levels.  His 2005 book, Trust and Rule, picks up on one particular feature of social organization that is often instrumental in political and social episodes, including especially in the everyday workings of predation and defense.  This is the idea of a trust network: a group of people connected by similar ties and interests whose "collective enterprise is at risk to the malfeasance, mistakes, and failures of individual members" (chapter 1, kindle loc 186). Here is a definition:

Trust networks, then, consist of ramified interpersonal connections, consisting mainly of strong ties, within which people set valued, consequential, long-term resources and enterprises at risk to the malfeasance, mistakes, or failures of others. (chapter 1, kindle loc 336)

A band of pirates, a group of tax resisters, or a village of non-conformists in a period of religious persecution fall in the category of trust networks.  The stakes are high for all participants.  On the other hand, the American Medical Association, the League of Women Voters, and the pickpockets who work the Gare St Lazare train station do not represent trust networks, though they have the properties of social action networks more generally.  There is little real risk for any particular physician even if other members of the AMA don't play their parts in a lobbying campaign.  The willingness of members of the extended group to commit their own actions to a risky common effort depends on their level of trust in other members -- trust that they will make their own contributions to the collective enterprise, and trust that they will not betray their comrades.  (French historian Marc Bloch belonged to a trust network, the French Resistance, that led to his death in 1944 by the Gestapo; link.)

The general idea is that there are numerous examples of networks of people who share substantial interests in common, and who have a high level of trust in one another that permits them to undertake risky joint activities.  Here is a more complete statement of Tilly's conception:

How will we recognize a trust network when we encounter or enter one?  First, we will notice a number of people who are connected, directly or indirectly, by similar ties; they form a network.  Second, we will see that the sheer existence of such a tie gives one member significant claims on the attention or aid of another; the network consists of strong ties.  Third, we will discover that members of the network are collectively carrying on major long-term enterprises such as procreation, long-distance trade, workers' mutual aid or practice of an underground religion.  Finally, we will learn that the configuration of ties within the network sets the collective enterprise at risk to the malfeasance, mistakes, and failures of individual members. (chapter 1, kindle loc 186)

Trust networks are particularly relevant in the context of efforts at violent extraction and domination -- both on the side of predators and prey.  Predators -- bandits, pirates, and gangs -- need to establish strong ties within their organizations in order to be able to effectively coerce their targets and to escape repression by others.  And prey -- farmers in ranch country, rural Jews in Poland, or home owners in central Newark -- are advantaged by the existence of strong ties of family, religion, or ethnicity through which they can maintain the collective strategies that provide some degree of protection.  But Tilly makes the interesting point that the workings of trust networks cross over both contentious and noncontentious activities.  Here is a general statement that frames much of Tilly's discussion in the book:

Noncontentious politics still make up the bulk of all political interaction, since it includes tax collection, census taking, military service, diffusion of political information, processing of government-mediated benefits, internal organizational activity of constituted political actors, and related processes that go on most of the time without discontinous, public, collective claim making.  Trust networks and their segments get involved in noncontentious politics more regularly -- and usually more consequently -- than in contentious politics. (chapter 1, Kindle loc 208) 

The idea of a trust network represents a different way of getting a handle on the contrast between self-interested agency and group-oriented agency, which in turn corresponds to "economistic" and "sociological" approaches to social behavior.  Is it interests or norms that guide social behavior?  By introducing the idea of a trust network, Tilly is able to find a position someplace else on the spectrum -- neither purely self-interested behavior nor routine normative conformance.  Instead, agents within trust networks behave as purposive, goal-directed actors; but they have commitments and resources that people in other social settings lack, and they are thereby enabled to achieve forms of collective action that are impossible elsewhere.  We might say that Tilly is offering an account of the microfoundations of collective action, or of a certain kind of collective action.

In line with Tilly's lifelong interest in taxation and state-building, the idea of resource extraction plays a central role in his analysis of trust networks.  A central theme is the struggle between the tax-collecting state and the elusive, tax-evading trust networks that exist in civil society.  "Rulers have usually coveted the resources embedded in such networks, have often treated them as obstacles to effective rule, yet have never succeeded in annihilating them and have usually worked out accommodations producing enough resources and compliance to sustain their regimes" (kindle loc 229).

It is interesting to connect this dialectic of predation and evasion with the arguments Jim Scott puts forward in The Art of Not Being Governed: An Anarchist History of Upland Southeast Asia (link).  Part of the effectiveness of the highland peoples of Burma in Scott's account is the density of their social relationships and a consequent ability to sustain a degree of collective resistance that would be impossible in a less dense society.  And, in fact, Tilly's analysis of the tactical situation of a trust network subject to the superior coercive power of some other entity is enlightening in Scott's story as well.  Consider these avenues that Tilly advances as collective strategies for protecting a given trust network against the pressures of the surrounding state: concealment, dissimulation, clientage, predation, enlistment into the regime, bargaining, and dissolution (chapter 2, kindle loc 794).  We can find examples of each of these strategies in Scott's analysis of Burma.  More pointedly, we can see instances of almost all these strategies in the current conflicts between the Burmese junta and the cease-fire groups such as the Kachin Independence Organization (link, link).

So what kind of analysis is Tilly offering here?  What is the use of this concept from the point of view of the social sciences, beyond the metaphor and analytical specifics? Are there concrete historical or sociological hypotheses in play?  Does this concept provide a better basis for explaining some puzzling outcomes than existing theories?  Or, possibly, is the concept of a trust network another example of a part of the sociologist's toolkit: an ideal-typical description of a real social mechanism whose workings can be discerned in a variety of contexts?

Tilly is relatively explicit about several of these questions.  To start: he does not believe that "trust networks" constitute a homogeneous social kind.  We cannot offer a general account of the essential features of a trust network (kindle loc 823).  We can do a certain amount of classification within the group of social configurations that we call "trust networks".  So "trust networks" are socially real, and we can use ordinary methods of social and historical inquiry to map out some of their properties.

Further, he believes, we can state some mid-level regularities about trust networks and political regimes: for example,

• Trust networks survive and hold off predators when they generate enough resources to reproduce themselves;
•  trust networks are absorbed into systems of rule when existing autonomous trust networks disintegrate or cease to provide substantial benefits; 
• variations in the kinds of trust networks that exist help explain the variety of the consolidation of rule that occurs in given settings. (loc 1096)
• trust networks that mark, maintain, and monitor sharp boundaries between insiders and outsiders generally operate more effectively than others (loc 1238)
• trust networks most commonly defend themselves from predation by adopting some combination of the strategies of concealment, clientage, and dissimulation (loc 1724)

Another important question is the role of evidence in this treatment.  Tilly offers dozens of examples of significant historical instances of trust networks at work -- as predators, as prey, and as potential subjects of extractive rule.  And we can ask this question: what is the evidentiary value of the examples?  Are they merely illustrative?  Do they serve to pinpoint some of the specifics of discrete social mechanisms?  Or are they more like suggestive heuristic cases that may point us in the direction of a more developed theory?

I think that Tilly's view would be something close to the second option here: the examples are valuable and insightful because they provide relatively transparent instances in which the mechanisms are fully exposed. They are a bit like the observations of "animalcules" through van Leeuwenhoek's microscope: glimpses of an underlying mechanism that proves to be an important constituent of more macro-level processes.

At the same time, the analysis doesn't add up to a "theory" of trust networks; it is more analogous to descriptive ecology than it is to the theory of the gene.  When Darwin documents the variety of finches in the Galapagos Islands, or when Wallace painstakingly describes the myriad distinct species of beetles he finds in the jungles of the Malay archipelago, each is involved in a kind of scientific work that stands between pure description and explanatory theorizing.  And this seems to be roughly where Tilly's dissection of trust networks falls as well.

It is also interesting to consider whether there are important examples of trust networks in the world today.  And it seems clear that there are.  The situation of the ethnic movements in contemporary Burma is one good example.  Domestic terror groups and right-wing militias provide another clear set of examples.  The American Civil Rights movement, the Freedom Riders, and SNCC's organizing efforts offer another good set of examples as well (link).  So the concept of a trust network is in fact a valuable contribution to the study of collective action and social mobilization.