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Original Research Article

Studying Sociocultural Networks

On the Viral Logic of Networked Media Objects

Fernando N. van der Vlist

(College of Humanities,) University of Amsterdam, the Netherlands

Working paper

Published online: 19 January 2013


This paper puts forward a theoretical framework to explore and understand the viral logic of digital replication and sociocultural contagion in an age of networks. It suggests an account of viral logic grounded in the Darwinian understanding of memes as well as in Tarde's understanding of imitation and Bourdieu's habitus. Using this framework, three specific classes of networked objects were analysed that operate through viral logic on the Web. These classes are activity streams, media conversations, and parasitic media. As a result of these analyses the theoretical framework was extended with a digital account to fit with specific properties of the Web. This research resulted in an applied understanding of viral logic, and of the networks that are shaped by the productivity of memes. It also led to a critical assessment of quantitative analysis, questioning in particular the asymmetrical relation between the social networks and the real world. To this end, a contextual methodology is suggested to complement quantitative analysis with a deep understanding of network mechanics.


network society, viral logic, social diffusion, habitus, platform mechanics, social streams, cultural analysis

network society
viral logic
social diffusion
platform mechanics
social streams
cultural analysis

1. Introduction

Contemporary society can be understood as a network society (Castells 1996) in which networks constitute the primary organizational model of action. Acknowledging the infectious quality of networked media objects, this paper suggests viral logic as a useful way to understand processes of sociocultural contagion in this society of networks.

In the first section of this paper I will discuss theoretical concepts that can be used to analyse memetic processes. It will discuss memetic research (Sampson 2012; Parikka 2007; Mandoki 2005; Orr 2003) and its origins in evolutionary biology (Dawkins [1976] 2006; Blackmore 2000), as well as a sociological account in terms of social diffusion (Tarde 1903; Rogers 1962; Lynch 1996; Kullenberg and Palmås 2009; Kelty 2008) and behavior of habit (Bourdieu 1984, 1990; Swartz 2002; Hilgers 2009). The second section shows specifically what kind objects can be understood in light of the established framework. Activity streams (Manovich 2012; Bucher 2012), media conversations (Manovich 2009; Bianconi 2012; Rourke 2012; de Jong and Schuilenburg 2006) and parasitic media objects (Parikka 2007; Barabási 2003; Biddle et al. 2003) will be discussed as mechanisms operating through a viral logic. In the third section, memes and viral logic will be critically discussed in terms of their measurable properties as cultural data (Shereen 2012; Murdoch 1997; Bod 2012; Poell and Darmoni 2012), raising important questions about the asymmetrical relation between social networks and the real world (Lovink 2012; Coleman 2012).

2. Theoretical Framework

In this section a conceptual framework will be established for understanding the infectious quality of network objects. It will discuss some key theoretical works that have been developed to analyse memetic processes and aim to provide one such new perspective.

2.1. Dawkins' Memes as Selfish Replicators

What theoretical tools have been developed to analyse and understand processes of cultural contagion? One approach has been set out by Richard Dawkins in his landmark publication of The Selfish Gene that was first published in 1976. In this book he introduces a biological approach to the phenomena of cultural transmission that leads to his proposal of memetic theory, derived from genetics. Memetic theory considers memes as analogous to genes, as replicators giving rise to a form of evolution. This kind of evolution, however, differs fundamentally from genetic evolution. “Examples of memes are tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches. Just as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation” (192). This not only shows the different process by which memes spread as opposed to genes, but it also points to the increase in speed that follows from this difference. Dawkins also emphasises that memes are not static, but are to be considered as living structures. It is alive because the imitative process by which memes spread make that the meme itself is always in flux, mutating over time into theoretically infinite variations. This is illustrated by the following: “if a scientist hears, or reads about, a good idea, he passes it on to his colleagues and students. He mentions it in his articles and his lectures. If the idea catches on, it can be said to propagate itself, spreading from brain to brain.” (192). Imitation, unlike genetic transmission, does not just take place between biological organisms, but is embedded within the complex dynamics of a society or community (e.g. the scientific community). Therefore, we need to turn towards sociology to complement this theoretical framework with a sociological account.

2.2. Tarde's Diagram of Imitative Rays

The work of French sociologist Gabriel Tarde is particularly relevant here. In his three key texts Les lois sociales: Esquisse d'une sociologie (1898), Les lois de l'imitation (1890), and La psychologie économique (1902–1903) he forwarded a theory of interwoven microrelationships for which he is now acclaimed as a forefather of both memetics and actor-network-theory (Sampson, 17). Tony Sampson has analysed Tarde's diagram within this context and emphasises that his theory of sociology should not be seen in either a macro- or a microreductionist way as for instance Durkheim did in his work. This is not to say that there is no larger unity, but that the microrelations themselves compose social unity. For Sampson, this is what makes Tarde's theory align with Deleuze's assemblage theory.

Tarde uses different terms (currents, waves, flows) to point to these microrelations, but for Sampson the notion of imitative rays as what “radiate[s] out imitatively” (Tarde 1903, 136) stands out. For him, the idea seems to capture the complexity of the social relation that Tarde aims to describe. He then goes on to further specify his preference for this particular term: “the imitative ray comprises of affecting (and affected) noncognitive associations, interferences and collisions that spread outward contaminating feelings and moods before influencing thoughts beliefs, and actions. Moreover, the imitative ray does not travel between (inter) individual persons; rather, it moves below (infra) the cognitive awareness of social association” (19). The statement above captures beautifully the central ideas on which Sampson's virality is based. For him, that which spreads imitatively should not be confused with a cognitive or ideological transfer between individuals or social groups. Instead, what spreads are noncognitive associations located below our conscious thinking and acting. This transforms the imitative process from a fully subjective concept into what Sampson calls a relational ontology. It is a social consciousness through which thoughts and ideas are not just transported from one place to another, but which forms the very essence of the epidemiological diagram. Tarde's understanding of social unity in terms of microrelations thus makes his work an important addition to understanding how memes as units of cultural transmission do not just travel between, but below our consciousness. This opens up a window to expand our theoretical framework with the work of another French sociologist.

2.3. Bourdieu's Sociology of Habit

The work of Pierre Bourdieu has become a key reference in theories that focus on human action as practices. His important concept of habitus offers a sociological understanding of actions as regulated by habit, emphasizing the unconscious yet pervasive role that habit and convention play in our daily lives. His theory helps us answer the question of how imitative action is regulated.

According to David Swartz, Bourdieu's concept grows out of criticism towards Lévi-Strauss' structuralism. According to him, structuralist explanations lack agency, and this is where Bourdieu's habitus “builds on the idea that actors act strategically and practically rather than as conformists to external sets of formal rules” (2002, 62). Bourdieu conceptualises human action as the interaction between habitus, capital, and field. By capital he means the resources that contain symbolic value to a field, which in turn is the social context within which habitus generates action. Habitus is defined as: “A system of durable, transposable dispositions, structured structures predisposed to function as structuring structures, that is, as principles which generate and organise practices and representations that can be objectively adapted to their outcomes without presupposing a conscious aiming at ends or an express mastery of the operations necessary in order to attain them” (53). Habitus functions like an underlying grammar that structures our virtually unlimited forms of action, and generates personal expectations and perceptions. As Swartz notes, it is generally not consciously reflective (63). The term dispositions in his definition suggests a “capability” and “reliability”, instead of a frequency or repetition (63). They are therefore acquired through methods of informal learning of social interaction such as gameplay and imitation. But Bourdieu also stresses the collective nature of his concept, because individuals are “never more than a deviation” from his or her collective reference (qtd. in Swartz 1990, 60). It makes that we experience a sense of social unity among members of a social class or status group, and also that we may sometimes predict particular behavior. It seems indeed true then, as Bourdieu noted, that much of our everyday practices function as self-fulfilling prophecies. Fundamentally then, it is not our rationality or biology that governs our actions, but rather our cultural habits. These cultural habits, once established, endure as part of a unifying “force of habit”, cannot easily be changed as they sustain and reproduce social order, and are not only constituted by past experiences of socialization but are also constitutive of ongoing practices (Swartz 66–67). Habitus thus provides us with a framework for understanding behavior as a cultural product that is both collective and individual at the same time, raising questions of power about the adoption of cultural habits and human actions.

2.4. Matching Receptors

Bourdieu's habitus is not only useful for understanding behavior, but it is also constitutive of the matching receptors that form the necessary condition for contagion from source to target. Katya Mandoki states that receptors emerge from what Jakob von Uexküll (1957) defined as the ümwelt or perceptual world of an organism (qtd. in Mandoki 43). Although Mandoki views memetics from a biomedical perspective, this particular concept seems a useful addition to the framework as it emphasises the need for something to connect to. For Mandoki, these are strongly held opinions that become receptors “through which the orator's ideas can penetrate the audience's attention, provoke sympathy and spread his message” (43). This means that the source agent must shape his message to match, penetrate and take advantage of available receptors to increase the effectiveness of the message. Indeed, “fabrication of messages with the calculated pattern to match receptors is a common practice in everyday face to face interactions as well as in the media, politics and various areas of social exchange; more specifically, in psychological engineering employed by marketing” (44). In this sense, the success of a meme is not so much dependent on internal characteristics of longevity, fecundity or copying fidelity (Dawkins 12–20; ch. 2), as it is dependent on its ability to match with habitus.

3. Viral Logic on the Web

Now that we have established a theoretical framework, we are able to apply it to contemporary objects found in new media, particularly on the Web. The following section will discuss aspects or mechanisms from three classes of such objects that are based on a viral logic.

3.1. Activity Streams

The first class of objects to be discussed here are RSS/Atom-based feeds such as Facebook's News Feed, Twitter's activity feed or FriendFeed. While these feeds are updated in real-time, new updates often pop up as fast as you read them, making the term activity stream more appropriate. Within this class, being part of the same real-time environment accelerates the memetic process by establishing an architecture that prefers sharing and visibility over invisibility.

In “Want to be on the top? Algorithmic power and the threat of invisibility on Facebook” (2012), Taina Bucher explores new modalities of visibility in a new media environment through an analysis of EdgeRank, the algorithm that “structures the flow of information and communication on Facebook's News Feed” (1). Bucher argues that Foucault's notion of permanent visibility is reversed in this environment, constituting a constant threat of disappearing from the stream and becoming obsolete. One of the interesting things about this analysis is the discussion of the many different components to this mechanism of algorithmic visibility caused by the EdgeRank algorithm. The mechanisms at play here constitute a digital habitus, constituted not through socio-cultural iterations, but rather through technical implementation of functionality. In this habitus, which is perceived by the user as the whole of possibilities within a system, behavior should also be thought of as being derivative from that system of functionality. Although iterative behavior might not be constitutive of a digital habitus, it does however constantly reinforce it. So what exactly are these functionalities? The obvious examples are functions such as sharing, commenting, and liking. However, these functions also suppose that every item that shows up in the News Feed is considered an object in itself, and that every interaction with that object is evaluated by a global mechanism (i.e. it applies to the whole environment unless shadowed) such as the EdgeRank algorithm. To refer back to Bucher's analysis, then, the architecture developed here establishes a specific environment with concrete mechanisms of action.

The mechanisms at play in Facebook's News Feed make use of a viral logic. Every functional component plays some role in the constitution of a digital habitus that forces behavior to follow this viral logic. To understand this, Marshall McLuhan's famous formula “the medium is the message” seems particularly useful, for he described the “content” of a medium as a juicy piece of meat carried by the burglar to distract the watchdog of the mind (1964). His formula can help us understand that the content and the mechanisms behind it can be considered as two different things that are not necessarily relating to each other. Consider for instance what Liking is all about. In an article for NRC Handelsblad, José van Dijck argued that social media do not require arguments, but just require basic (read universal) spontaneous emotions. Consequentially, visibility is determined by quantitative popularity, predictability and exploitability (18). This particular imitative mechanism, then, requires emotion-oriented matching receptors. Each individual execution of the Like-function reinforces not only this specific mechanism, but, for instance, also the commercial success of Facebook.

3.2. Media Conversations

The second class of objects to be discussed here centres around the notion of a shared frame of reference. This is where we find the ubiquitous snippets of popular culture captured and spread in the form of animated GIFs, screenshots accompanied by short messages, viral videos and the whole realm of framed Internet cats. Within this class, the shared frame of cultural references provides matching receptors.

As Lev Manovich observed in his article “The practice of Everyday (Media) Life: From Mass Consumption to Mass Cultural Production?” (2009) content, news or media within the context of social media platforms become tokens used to initiate or maintain a conversation (326). Their original meaning, in this sense, is less important than their function as tokens. He then continues his argument to develop the notion of media conversations, which he understands as “a conversation that takes place through images or video—for instance, responding to a video with a new video” (328). He then notes that this is phenomenon is not limited to web-based environments:

Jean-Luc Godard reacted to Hollywood-style narrative cinema, and so on. To use the terms of YouTube, we can say that Godard posted his video response to one huge clip called classical narrative cinema. But the Hollywood studios did not respond—at least not for another thirty years. (328)

The example Manovich uses here is particularly interesting as it illustrates what it means to reply to a conversation, following a memetic logic. It may help to give another example here. In his article “GIFability”, Giampaolo Bianconi writes that Dan Harmon, who is the executive producer of the television sitcom Community, tries to: “many times a season to put Alison [Brie] in a situation, wardrobe-wise, that I know is going to end up as an animated GIF file.” (2012). This example shows how Harmon takes into account the viral logic of the Web and the tries to figure out the language that its users speak (i.e. their matching receptors). It also shows that not everything works as a meme (e.g. they are small, easily understood and often funny units), and that the individual episodes react to the users. It is important to observe, then, that these memes can only work because there is a shared frame of reference constituted by the producers of Community that is needed to understand and appreciate such memes.

Now what exactly is spread in this class of objects? Considering again that iterative behavior is constitutive of habitus, it is not only the content of the meme that is repeated, but also the implications following after it. First, according to Michael Hardt and Antonio Negri, for instance, the age of globalization is also the age of universal contagion (2000, 136, qtd. in Parikka 2007, 1). Conversely, this implies that viral logic, when applied to cultural phenomena, will ultimately lead to a global culture. Put differently, it leads to a global habitus. Second, what is being reinforced through this memetic process is not the labor of producing a meme or successful television sitcom, but rather the communal experience of spectatorship or postproduction (Bianconi). Third, the idea that producing a media object is subordinate to its survival in a viral logic environment reinforces that particular type of network.

3.3. Parasitic Media

The third class of objects to be discussed here concerns the technical infrastructure of the Web. Objects in this class are characterised by their parasitical relationship with their hosts, examples of which are computer virusses, peer-to-peer computer networks, electronic spam servers and database-backed Web applications such as Google AdSense. Within this class, just being connected through a technical infrastructure means being subject to a parasitical mode of contagion that activates just by being part of it.

What is important to note, as both Jussi Parikka and Tony Sampson underline, is that memetic processes should be read in connection with their environments, that is, the quality of the network (Sampson 2007; Parikka 2007, 305). Not every network abides by the same rules, and the viral cannot simply be equaled to a rhizome. Parikka – in the footsteps of Barabási – argues in “Contagion and Repetition: On the Viral Logic of Network Culture” that “[computer] viruses as specific objects can be used to reveal hierarchies”, because networks are “modelled according to the 80/20 ratio principle, where 20 percent of the nodes have connections with the remaining 80 percent, making the network very aristocratic.” (Parikka 305). Basically, this tells us that some nodes in the network increase the amplification of the imitative ray more than most of the others. Computer viruses are simply programs that replicate themselves while they travel from one computer to the next. Doing this, they are parasitical to their hosts, gaining access to the technical infrastructure. Although this is a purely technical process, it requires the same matching receptors; in this case that means technical compatibility. This aspect, however, is not limited to computer viruses, because GIF images or other digital media objects require this technical compatibility just as much as viruses do. In fact, viruses are sometimes cloaked as media objects. A worm virus called W32.Perrun, for example, attempted to infect JPEG and TXT files to append its malicious content to other files (Knowles). These objects are parasitical not only in a technical way, but also to their form as media object.

A second example in this class is Google AdSense, which is a web-based application that is parasitical in the sense that it aims to automatically serve media adverts that are target to both site content and users. For this to work, these services require information about these users, often resulting in extensive profiles. This database of information is then basically used as a huge set of matching receptors to which content may be targeted. This way, contagion has a better chance of being successful, as this user profiling has provided insight into the frame of reference of these users. An interesting side note here is the Google Will Eat Itself project. With this cynical project, the developers Alessandro Ludovico and Paolo Cirio make a statement by automatically buying small bits of Google via their own advertisements. The description of the project reads as follows:

We generate money by serving Google text advertisments on a network of hidden Websites. With this money we automatically buy Google shares. We buy Google via their own advertisment! Google eats itself – but in the end “we” own it!

Although it would take approximately 202,345,117 years from now before they will fully own Google, the example does show a two-way potential of parasitic media.

4. Cultural Analytical Research of Social Streams

As we have seen above, the mechanisms underlying platforms are constitutive of their memetic success. In the following section we will critically discuss how memes and viral logic can be used to gain insight into social networks using a hybrid of sociocultural and technical analytical research. It will be argued that there is an asymmetrical relationship between the social and the social network, and that we need to add a contextual account to quantitative research in order to understand the shape of the network.

4.1. The Productivity of Memes

When raising the question in what way memetic processes can tell us something in terms of their results, it is important to first consider what kind of results we are presented with. What we often see is the measuring of viral processes in terms of quantitative results. For this purpose, many different mapping software tools have already been developed. Among these mapping tools we find for example Citeology: Visualizing Paper Genealogy, which is a data visualization project developed by the Autodesk research department that visualises the relationship between research publications by graphically connecting a large set of papers through their use of citations. Another example is The New York Times' Twitter Cascade, developed by their research and development department. This project aims to visually represent what happens when readers (re)tweet about shareable objects. On the project page, the creators write: “This first-of-its-kind tool links browsing behavior on a site to sharing activity to construct a detailed picture of how information propagates through the social media space”. Such a tool can thus visualise quantitative data, capturing complex flows of information and revealing movements and connections between nodes in ways that someone like Tarde could only have dreamed.

Several things are important to realise here. First, results capturing memetic processes are often quantitative. Second, that this data often comes from “big data companies” such as Google, Facebook, Twitter, Apple, because quantitative data becomes more precise (read meaningful) when related to massive datasets. And third, that memes can play a productive role as data-generating replication mechanisms. Social media platforms know this. It becomes a mechanics, which underlies the platform. Indeed, this is basically Tarde's theory of the imitative ray applied to social media platforms.

4.2. The Social in Social Media

Since this research is particularly related to quantitative studies of social media, we should also critically review the notion of the “social” in social media. In his piece “What is the Social in Social Media?”, Dutch media critic Geert Lovink asks exactly this question. He states that: “The social is no longer a reference to society – an insight that troubles us theorists and critics who use empirical research to prove that people, despite all their outward behavior, remain firmly embedded in their traditional, local structures” (2012). This statement follows from the question whether we use the social platforms only to share information, experiences, and emotions, or whether we also use it to get together in real life and form “social swarms” (2012). The observation that the social now manifests itself in different ways raises the question about the shape of the social. According to Lovink, this shape can be found in the network itself. This is precisely why the viral logic of memes is so useful to network analyses. Memes can produce a map of the actual shape of these networks, a bit like an echo scan of the body. Related to this purpose, there is currently a trend in network visualization that has been going on for a few years now to gain insight into these abstract networks. Still, however, it is important to realise that this type of analysis leads to specific concerns.

4.3. Studying Social Streams on the Web

There is, nevertheless, great potential in the analytic properties of social media objects. Transmedia artist VJ Um Amel (Laila Shereen) recognises this as well in his article “Studying Social Streams: Cultural Analytics in Arabic” (2012). Shereen argues that the stock of “primary data” (actual tweets, status posts, and so on) is important for nuanced cultural analyses, but that most analyses of social media phenomena don't take into consideration the use of different languages (2012). A first point of concern about the accuracy of this kind of analysis comes from American statistician Edward Tufte. He observed that “you will always find what you are looking for.” (qtd. in Shereen 2012). A second point of concern is that such analyses do not provide much more information nor the significance of contextual factors around these phenomena. These concerns result from the fact that this kind of data concerns borne-digital media, that is phenomena that have no absolute relation to the actual real world. As Manovich put it a bit more nuanced: “Often content, news, or media become tokens to initiate or maintain a conversation. Their original meaning is less important than their functions as tokens” (2009, 326). What we need to do is connect cultural analytical research from computational perspectives to sociological perspectives such as Bourdieu's notion of Habitus. First of all we need to realise that data visualization and statistical analysis cannot provide us with a complete map of a network, it can only show us one perspective. Second of all, we need to provide what Clifford Geertz and others have called “thick descriptions” (Geertz 1973, 3–30; ch. 1; Murdoch 1997, 91–98; ch. 9), describing both a quantitative pattern, and its sociocultural and technical context. Using memes as the foundation of such research can provide insights not only into the technical shape of a network, but also into its context by adding an understanding of cultural and digital habitus, and of media platforms and the mechanisms by which they operate.

5. Conclusions

Viral logic proves to be particularly suited to function as an efficient underlying mechanics of, for instance, online social network platforms. By providing a theoretical framework that draws from the Darwinian paradigm as well as from sociology to understand social diffusion, we are able to understand better the mechanics at work in social platforms on the Web. Examples we discussed in this context were activity streams, media conversations and parasitic media. While discussing these specific classes of objects it became clear that Bourdieu's notion of habitus had to be extended slightly so it could also be applied in contexts that are governed by technical or protocological laws. In a similar way, we also extended Tarde's theory of imitative rays by concluding that it functions as a mechanics, which underlies a social platform such as Facebook. Memes as semi-autonomous units were discussed in terms of their function as objects that capture memes through different media (e.g. an animated GIF, or computer virus), but more important was their function as a networked object, that is its ability to productively constitute networks via matching receptors and habitus. This conclusion then led to a critical perspective on quantitative analysis, questioning in particular the relation between a network and the real world. With that in mind, a methodology was suggested that intersects between quantitative analysis and a deep understanding of its sociocultural and technical context. With this purpose in mind, this paper has provided a theoretical framework.

This paper has attempted to argue why it is important to question underlying mechanics of a platform, and how to critically assess what is really represented by a dataset in this context. It should be noted that the concepts presented here are focused, but not limited to studying sociocultural networks. Networks are the key organizational models of action in a network society, but not every network abides by the same rules.

6. Acknowledgements

A small word of thanks to Michael Dieter and Bernhard Rieder for their inspiring seminars and lectures on new media analysis. The sessions on platforms, network theory and cultural contagion were particularly helpful. I am also grateful to Anlieka Marconi for taking the time and effort to look over the spelling and grammar of this essay, and for pointing out some citation-related inconsistencies.

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Title: Studying Sociocultural Networks
Subtitle: On the Viral Logic of Networked Media Objects
Type: Research article; Assignment F. N. (Fernando) van der Vlist
Author.affiliation: College of Humanities, Faculty of Humanities, University of Amsterdam Dr. M. J. (Michael) Dieter; Dr. N. A. J. M. (Niels) van Doorn
Instructor.affiliation: Dept. of Media Studies, Faculty of Humanities, University of Amsterdam
Abstract: This paper puts forward a theoretical framework to explore and understand the viral logic of digital replication and sociocultural contagion in an age of networks. It suggests an account of viral logic grounded in the Darwinian understanding of memes as well as in Tarde's understanding of imitation and Bourdieu's habitus. Using this framework, three specific classes of networked objects were analysed that operate through viral logic on the Web. These classes are activity streams, media conversations, and parasitic media. As a result of these analyses the theoretical framework was extended with a digital account to fit with specific properties of the Web. This research resulted in an applied understanding of viral logic, and of the networks that are shaped by the productivity of memes. It also led to a critical assessment of quantitative analysis, questioning in particular the asymmetrical relation between the social networks and the real world. To this end, a contextual methodology is suggested to complement quantitative analysis with a deep understanding of network mechanics.
Keywords: network society, viral logic, social diffusion, habitus, platform mechanics, social streams, cultural analysis
Length.words: 4,596
Length.reading: 26 mins
Date.submitted: 11 Jan. 2013
Date.publishedonline: 19 Jan. 2013
Date.evaluated: 30 Jan. 2013
Language: English (United Kingdom) Modern Language Association (7th ed.)
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