Part III: Moving beyond the discrete to study the space of flows

Annette Markham

Jan 17, 2012


(From network analysis to network sensibilities: Part III)

Part I
Part II
Part III here

Moving beyond the discrete to study the space of flows

Consider some of the persistent notions that arise in multiple disciplines over the past few decades: That what we consider an organization is a momentary freezing of flux and transformation (Morgan, 1986), which we can only identify through retrospective sensemaking (Weick, 1969); that space is the crystallization of time (Castells, 1996, p. 411); that the ‘individual,’ far from being a universal concept (e.g., Strathern, 1992), is one that is only understood in terms of relation and interaction (e.g., Blumer, 1969); or that both micro or macro elements of ‘the social,’ such as individuals and institutions, respectively, are nothing but networks (Latour, 1997, 2005). All of these ideas call for reconsideration of what is conceptualized and captured as the object of analysis. Pushing this further, decades of epistemological discussions challenge us to consider whether “object of analysis” is the best conceptual frame for engaging in what Rabinow and Marcus call an “anthropology of the contemporary” (Rabinow, Marcus, Faubion, & Rees, 2008).

Despite our acknowledgment that phenomena and research situations ought to be considered more fluidly, qualitative methods are historically designed for use in physically situated, local, fairly static contexts. As noted by Rees (Rabinow et al., 2008), “anthropologists are increasingly studying timely phenomena with tools developed to study people out of time” (position 10).  It remains easier to focus on the outcomes rather than the processes of interaction. Traditional analytical tools are object oriented—focused on those obdurate qualities of the phenomenon that can be identified, parsed, recorded, displayed for other researchers and scrutinized as discrete units of data.

For me, network perspectives provide tools for shifting from object to flow, or structure to relation. Although many network analysis scholars promote the idea that “the focus of network level analysis is on the properties of the network as a whole” (Brandes & Earlbach, 2005, p. 6), most of the practice itself depends on an orientation toward processes of connecting, interacting, and relating. This everyday stance can allow the analyst to focus on the intensely relational social actions that create these flows, or on the flows themselves. I review below some of these practices.

Visual and nonlinear sensemaking

The first step for me is to push past an embedded textual centrism to engage the phenomenon as a moving, sensory body. This involves at minimum using more visual models for sensemaking. Using visualization techniques at a very simple level, by drawing lines between ideas, promotes sensibilities not inherent in textual analysis. Some of this gets accomplished coincidentally when we write notes that include such things as circles around related elements, spaces between elements that illustrate the spatial characteristics of the phenomenon, or connecting lines to denote relationships among people, places, things, or ideas. But because it is not a deliberate practice, it is for the most part not systematized or scrutinized as a method. If we apply McLuhan’s argument that the use of any medium extends a particular sense and simultaneously amputates other senses to our own analytic tendencies, the value of attending to this traditional mode of research practice becomes clear. Writing by hand, typing on a laptop, drawing, listening; each of these media privilege certain senses (Chandler, 1992).  The more media we utilize to make sense of a phenomenon, the more we can potentially identify and disrupt our predispositions and limitations in categorizing discursive patterns, people, contextual features, or social structures. This point is certainly not specific to studies of contemporary internet-mediated culture.  Indeed, it is a concern made more relevant as our everyday practices of research have shifted from analog to digital, whereby our modes of sensemaking are more locked into ephemeral, non physical, cut and paste, linear, text driven media. It is fruitful to consider what might be lost and (re)gained by broadening our scope for acceptable and expected everyday practice.

Concept mapping is one way to think about this process.  As a graphical representation of the relationships among concepts, it enables the researcher to see an overview of a knowledge network, add new concepts or ideas, and focus on the relationships and connections among concepts.


Figure 14. Screenshot from a concept map showing the key features of the process of concept mapping. (Novak and Canas, p. 1)


Used systematically and iteratively as a form of qualitative analysis, concept mapping can sponsor less linear or text-centric sensemaking. The practice functions at both a direct and meta level,[1] but we can also say that it represents the practice of learning connected to so-called “digital natives:” Grazing, deep diving, and feedback loops (Palfrey and Gasser, 2008, p. 241).

At the direct level of analysis, this might involve creating a range of concept maps by hand and then rearranging elements. This practice is not uncommon and there are many techniques, each unique to the individual researcher’s preferences. Yet as a tool for data analysis, it remains sidelined as a precursor to more guided forms of textual analysis. Developing and sticking to a systematic and consistent practice will yield a much richer outcome. For me, the physical act of drawing, connecting, and rearranging is essential. Cutting apart these maps and moving the scraps of paper around on the table physically helps me reconsider relationships and dimensions of experience.[2] In looking at visual representations of the complexity of personal connections, I get a different sensibility than when I review transcripts of interviews with individuals who have stepped out of this complexity to engage in a one-one conversation with me, a researcher, who guides the conversation in the directions I think are important, even as I design an open-ended set of questions and seek to be purely inductive. I understand a situation differently if I can visually see direct and indirect lines of influence, or look at how nodes of power and isolation remain static over time or shift in meaningful ways. This is possible to see in text also, but visual renderings add a difference that arguably makes a difference in the analysis.

As mentioned earlier, multiple, iterative renderings are crucial to the process, to avoid over determination or reductionist mappings.  I can also take any particular element and “deep dive” into it, exploring it more fully and following new paths. Taking time to draw new renderings throughout this process transforms the informal practice into a systematic method. While I can certainly experience the chaos of technological saturation and multphrenia at a visceral level and then think about it, meaning takes different shapes when I see multiple possible networks played out from different center nodes, over different time periods, or through different perspectives. This is not to suggest that I am gaining a more complete picture. It is rather a stronger sense of the complexity as I witness different patterns or connections beyond my own ability to observe. My comprehension is also more fully realized when I do not erase versions of my interpretive maps, but review the way my conceptualizations have shifted over time.

From outside to inside

At another level, I find network maps useful in conceptually shifting the researcher’s relationship to the data from outside to inside. Words in sentences create logics strung together in syntax.  Images allow one to look at elements in nonverbal or spatial terms. Simplified such, a network map provides a snapshot of salient relational characteristics and patterns. Three dimensional or animated maps add further complexity. Zooming in or out and moving around to focus on various curiosities takes me into the pattern. Of course, sophisticated data visualizations are not always available to the qualitative researcher whose inventory of skillsets likely does not include mathematical modeling and software rendering. Sitting at my desk with paper, pencil, and a laptop, the perspectival shift is more a matter of empathy and imagination.  To work around my technological limitations in creating complex network maps of my own data, I systematically search for visualizations that represent the concepts.

At this level, it matters less where you go than what you do with what you find along the way. If we can become attuned to the multiplicity of experience and the infinite possibilities for identifying and analyzing cultural practice, the analytical outcome can become a discussion point rather than an attempted explanation of the whole. Once this perspective is embraced, it becomes possible to move differently (and more freely) to conduct complex analyses of the social. Notably, while this stance implies an epistemological shift of sorts, this is not necessarily warranted.  The techniques may be a supplement to other forms of analysis.

From individuals to networks

Actor network theorists ask us to consider that contemporary culture requires a shift from actor to network. Individuals are defined by their networks: “An entity is entirely defined by the open-ended lists in the databases” (Latour, et al, 2012, p. 3).  From this perspective, anything we might call an individual is simply a temporary constitution of attributes. Likewise, what we might call a social structure is an assemblage of common, and possibly persistent, sets of attributes. To make sense of these assemblages, it is not necessary to explain the whole or conduct a holistic study of a bounded field. Rather, it is possible to start anywhere and follow the data — attributes, profiles, persons, memes, or other salient units of information. In some ways, it doesn’t matter where one begins because one will always find only parts, as these are much greater than what we might describe as ‘the whole.

From ‘a priori’ to ‘stumbled upon’ categories and boundaries

This idea provides a sensible approach in what seems to be more and more complex research situations. As every context is interwoven with and into incomprehensible and ever changing information networks, it is unnecessary to identify boundaries and categories in an a priori fashion. In a provocative recent study, Latour and his colleagues (2012) provide multiple examples to demonstrate how it is possible to allow the relevant dynamics to emerge as one surfs these networks: “Instead of trying to simulate and predict the social orders, we wish to acknowledge the limitations of the simulation approach for collective systems and prefer letting the agents produce a dynamics and collect the traces that their actions leave as they unfold so as to produce a rich data set” (Latour, et al., p. 13).

This parallels findings in mathematics and physics that demonstrate that complex systems can be understood by focusing on parts and interactions among elements, starting from almost any point or perspective in the network. Patterns emerge, despite seeming chaos or randomness (Buchanan, 2002, p. 185). Considering the experience of digital navigation through endless informational pathways, the research challenge is therefore not to consider how to narrow the choices in order to comprehend the whole but to reconsider the notion of ‘the whole’ altogether.  Take for example the way we automatically draw boundaries around the object of inquiry based on our taken for granted understanding of how the individual and the social are linked together as part to whole. Our choice about where to begin often emerges from either end of this dynamic.

A Facebook friend network, for instance, is commonly determined by centering an individual and reaching out to find all his or her friends.  A study of Facebook users might also start at the other end of the spectrum, by defining the larger social structures to which individuals belong (youth, hate groups, fans of X or Y, and so forth) and then constructing datasets from the networks that emerge from these interest nodes

Likewise, although an online community may be determined by official membership, it is often determined by assumptions about larger structures, such as ethnicity, age, nationality, or gender.  It might be delineated by types of participation, which could be operationalized in such ways as contributor, author, commenter, or lurker. Alternately, one could define the community on the basis of levels of participation, from core (heavy) to tertiary (occasional) participants. It can also be defined by types of content produced by members.

The decision to draw definitional boundaries around the research object prior to its study is rarely random and the rationale is often pragmatic. But what are the underlying epistemological assumptions? Is there something essential about the whole?  Is it inevitable that individual elements, put together in some way, will comprise a structure? What if we can no longer take systems theory for granted as the way the world works?  What if, as Latour (2012) and his colleagues suggest, the whole is always less than the parts?  Again, the difficult shift for me (or anyone steeped in epistemologies that link individuals to structures, who seeks to identify cultural patterns through the systematic analysis of discourse produced among pre-defined groupings of individuals in order to create explanatory or thickly descriptive accounts), is how to radically reconsider the notion of ‘the whole’ at the level of data collection, analysis, and interpretation. If focus on process, association, connection and movement is the goal, it requires shifting from matters of fact to matters of concern (Latour, 2004, p. 9). The importance lies in the questions that emerge through the research practice of moving, as the individual or the social no longer exists from this perspective and need no longer be used as the unifying or bounding feature of a research project.

Multiplicity in meaning

Guided in many ways by the work of George Marcus (1998), ethnographers have been challenged to move away from extremely localized study. As discourses move more globally, the notion of multiple locations (multi-sited ethnography) gives way to multiple sites of situated meaning and ongoing processes of what Rodriguez calls “culturing” (2002). Appadurai (1996) proposes five ‘scapes’ as a way to consider streams or flows that are always at play in constructing cultural formations. These give practical dimensions to the analytical product of one’s movement with and through various data streams and networks. Using the idea of a photographer or painter wanting to capture a ‘landscape,’ we begin to build a sense that depending on innumerable variables, the picture will change.  It might be, as we can see in Claude Monet’s Haystacks, the time of year, our situatedness, time of day, or the medium for capturing the moment. This notion is useful as an analytic tool for obvious reasons, in that each iteration causes the researcher to reconceptualize, perhaps radically, the general description of the context and phenomenon, as well as the specific variables influencing the cultural snapshot. Mapping ‘scapes’ helps us envision cultural activity composed of various dimensions of global flow. Each type of scape can focus on a particular type of information flow, a particular person, a particular moment, and so forth. Almost any word could precede the suffix ‘scape’ to brainstorm types of maps to experiment with. Appadurai (1996) describes ethnoscapes, mediascapes, financescapes, technoscapes, and ideoscapes, but there’s no need to be limited to these, as they are in this usage simply tools for thinking about multiple sites of meaning through networks and mapping.

In sum, a network perspective can prompt a methodological and perhaps epistemological approach that better resonates with the study of what is described as cultures of flow. To oversimplify my own approach at this point in time, this involves more visual rendering: Recording and treating as data more of the conceptual and experimental mappings that might otherwise be dismissed as brainstorming ideas, sorting data, or narrowing the scope of the study. It is not just a process that involves mapping, however. It involves a sensitivity to movement and connection, both in the phenomenon and in the researcher’s relationship to this flow.  The goal is to embody the perspective of moving with and through the data, rather than standing outside it as if it can be observed, captured, isolated, and scrutinized outside the flow.


[1] An overview of the theory behind concept mapping is well developed by Novak and Cañas (2008)

[2]There are many computer-aided tools for concept mapping, but having experimented with many of these over the past decade, I have found it much more productive to use pen and paper. I can work quickly, drawing and overlaying multiple maps without getting distracted by the added bells and whistles of software programs, or by certain technical demands and glitches.

Works Cited

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