1.
All a-Twitter: power and control in the
sociodigital age
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Abstract
This dissertation examines the mechanisms of power and control within the
social networking site Twitter. Using Twitter as a metaphor for the greater
Internet, we assess the structural and use-related elements that contribute
to the establishment of control in a networked environment. We do so by
investigating, from a theoretical standpoint, the various ways in which
information and data can be directly or indirectly controlled within the site,
before addressing the real-world implications of this. In doing so, we
approach three key facets of the site’s operation: (1) the technical control
of networked interaction; (2) the nature of networked conversation; and (3)
social hierarchies within the site. This dissertation proposes a model for
understanding the nature of power in an online context, whereby technical
limitations and freedoms, sociocultural capital and structural bias each
comprise part of a much larger paradigm of information control.

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Table of contents
Introduction ........................................................................................... 3
Theoretical approaches .......................................................................... 6
An initial Foucauldian assessment ....................................................... 17
The conversation .................................................................................. 23
Toward a social structure of Twitter .................................................... 31
Conclusions........................................................................................... 38
Works cited ............................................................................................. 41

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Introduction
Power is the most fundamental process in society. … What is valued and
institutionalized is defined by power relationships
(Castells, 2009, p. 10)
Much has been written in the last decade or so of the ‘free web’ – the idea that
online communication is, by its very nature, “emancipatory” (Morozov, 2011, p.
18). No doubt this is true in many ways. Many are optimistic, for example, that
new media technologies’ natural decentralisation will enable social movements
and activist groups to “self-organise” more easily and efficiently, as seen in G8
protests and the Zapatista movement in the last ten years (Holmes, 2008, p.
525). However, with new communication technologies also come new means for
the exercise of power and control. Indeed, the fluid and easily movable, but also
concrete and finite, nature of digital data create new challenges and
opportunities for this. It is of the utmost importance, therefore, that, as a
generation moving into an era of unprecedented digital immersion, we
understand how the mechanisms of power work in an online setting.
In this context, the microblogging service Twitter provides an excellent
case study. The website can be thought of as a complete social media network.
More than sites like Facebook, whose networks are at least partly enclosed and
private, and YouTube, whose capacity for networking is severely limited, Twitter
represents a highly public and open form of social organisation. While some
users have their profiles set to ‘private’, public discourse and conversation are
the key elements in the site’s broad raison d'être. As any user can ‘follow’ any
other user, provided their profile is public, without their express consent, the
network lacks the inefficiencies inherent in sites with more private networks,
such as Facebook. Unlike these websites, Twitter allows for both active and
passive connection, as there is none of, for example, Facebook’s requirement for
mutual action in establishing a ‘friend’ link between two accounts.

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Uniquely, Twitter is both a form of social organisation and a media outlet
in its own right. As an incredibly powerful tool for the dissemination of
information – among other things, it is a common source used by journalists
around the world – it can be conceptualised as an essentially 21st
-Century
primary source of information. Indeed, as long ago as 2009, 47 per cent of
surveyed journalists used Twitter to assist in writing stories, with 70 per cent
using social media more broadly (Maul, 2009). An analysis of the website’s
combination of information and socialisation can illustrate how power functions in
the digital realm. More than any other of the recent wave of social network sites
(SNSs), Twitter combines the human needs for social connection and new
information. As of June 2011, there were well over 200 million tweets being sent
every day – a huge amount of information – making it an incredibly potent
medium for the dissemination of data (Solis, 2012).
As Twitter is a relatively pure information source – insofar as it is
accessible to almost anyone, and therefore representative of the full gamut of
human bias, corruption, error and the like – it is an excellent source of
information about people’s relationships with technology and society. The site’s
almost non-existent moderation and remarkable level of openness make it
extraordinarily representative of the Internet as a broader entity – an open,
easily-accessible network built around inherently limited protocols of data
transfer and transmission.
The basis for this research is the belief that information and power are
closely related. The idea that knowledge both constitutes and is a by-product of
power – a concept at work in much of the discussion herein – is increasingly
relevant in a world built around the technologies of information. The conduits
through which we receive information are our basic sources for knowledge about
the world. They bear responsibility for the ways social, cultural and political
discourses develop, and are consequently the cause of much of the political
landscape’s formation.

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In this study we will split our discussion across three key areas: (1) the
technical control of networked interaction; (2) the nature of networked
conversation; and (3) social structures within the site. In the first case, we will
apply a theorisation based on Michel Foucault, Alexander Galloway and others to
the website’s use. In the second, we will seek to establish a model for interaction
on the site, and analyse its consequences. And in the third, we will posit a model
for a social structure within the site, and assess its impact on the behaviour of
information. In each case, we must seek to answer one key question: in whose
hands does this structural element put power? By doing this, we hope to provide
a means for the further study of power relations in the digital realm, not only
within social networking sites, but across the Internet more broadly.
It is important to note at this point that this is not an exhaustive study. In
a field as obviously subjective as this, it is counter-productive to speak in
absolutes. Rather, this dissertation will use a study of Twitter’s architecture as
the basis for the construction of a model to explain the way structural power
works in the network age. As such, this study will not address direct, individual
power relations and their functions. Rather, it will seek to analyse trends in aid of
a more holistic view of the ways in which Twitter can teach us about the
functions of power in the digital age.
In an ever more fast-paced and confusing world, it becomes more and
more important to understand how technologies can facilitate and cause the
establishment of structures of control. As long as we are unable to conceptualise
the mechanisms of power, we are fundamentally handicapped. The more we
understand about this increasingly digital world, the more effectively we can
operate within it.

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Theoretical approaches
In order to adequately understand the ways in which Twitter forms and regulates
power relations, we must begin by establishing a theoretical framework within
which such an analysis can take place. This will rest on twin foundations:
theories regarding the behaviour of data and information, and conceptualisations
of power and control. The former is important because Twitter is, at a
fundamental level, built on the movement and transmission of data. The latter is
essential in synthesising a model of power and control appropriate to the
information age. This study lies at the nexus of these two areas. With
information becoming increasingly vital to the functioning of our ever more
networked society – and, as we will see, to the global economy – an adequate
comprehension of the relationship between its behaviour and the mechanism of
power is crucial to our understanding of our almost fully globalised, digital world.
Before exploring these concepts, though, it is important to note that it is
impossible to fully separate what happens online from what happens in what we
might call the ‘real world’. We must remember that networked action does not
take place in the abstract – it happens within a context created by what has
occurred both off- and online. Because of this, any analysis of the online world
must take place within, and interact with, the broader context provided by
communication technology. It is important to gain a broad understanding of how
power works, and then to apply it to the online environment. Similarly, we must
also remain aware that mechanisms of control do not work in isolation – for
example, surveillance, as will be explained, does not occur in complete
separation from Foucault’s other means of control. The elements contributing to
the exercise of political power are in a state of constant, but ever-developing,
interaction with each other.
According to the Spanish sociologist Manuel Castells, the network –
broadly defined as a set of interconnected points or ‘nodes’ – is effectively the
basic unit of modern society. Castells articulates his view thus:

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As an historical trend, dominant functions and processes in the Information
Age are increasingly organized around networks. Networks constitute the
new social morphology of our societies, and the diffusion of networking
logic substantially modifies the operation and outcomes in processes of
production, experience, power, and culture.
(Castells, 2010, p. 300)
This “diffusion of networking logic” has wide-ranging implications for the
behaviour and spread of information. Among Castells’ key theses is the idea that
improvements in communication technologies have caused the network to
become the most efficient form of social organisation, in many cases replacing
more hierarchical, top-down forms (p. 301). This causality, the idea that
improvement in the technologies of information has led to significant societal
reorganisation, is crucial – it tells us that access to and distribution of data is
fundamental to society’s structure. Thus communication technology becomes a
useful starting point for a consideration of the functions and relations within
society. Viewed through this prism, we will see that the behaviour of information
within these technologies can be used to explain the workings of the
postmodern, digitised world.
At the core of this is the idea that the information technology revolution of
the mid-20th
century led to what Castells refers to as a “capitalist perestroika” –
an IT-led shift toward a fully globalised digital economy, within which the ability
to transmit data across the world in a fraction of a second allowed global
markets to function in increasingly efficient ways (p. 18). According to Wayne
Hope, as a result of “global finance [being] mobilized by business information
networks and public news networks,” “more currencies, more diverse and
complex financial assets are traded more frequently at greater speed and in
substantially greater volumes than in any previous historical epoch” (Hope, 2006,
p. 277). As the explosive growth in high-speed digital communication facilitates
ever more financial transactions, information technology is becoming a more
integral element in the global economy than at any previous point in history. This
is the key fact underpinning the notion of the ‘Information Age’ – with the

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acknowledgement of globalised IT as the technological basis for the world’s
economy comes a realisation that digital communication technologies are
increasingly coming to define life itself in the postmodern word.
One of the central concepts within Castells’ work is the notion that
information behaves in a very specific way within networks. He argues that
“networks process flows”. Flows, in this context, are “streams of information
between nodes, circulating through the channels of connection between nodes”
(Castells, 2009, p. 20). This idea contains two key elements. First, we have the
idea that information is not necessarily discrete and definite. While data is
transferred through networks in discrete ‘packets’ – the base unit of online data
exchange (Denardis, 2009, p. 2) – there is still a constant flow of information,
whether fast or slow, between the nodes in a network. Second, and most
importantly, we see the inherent rigidity of the network. No matter how
dispersed or non-hierarchical a network is, there are finite, well-defined
pathways through which data can travel.
Road networks – to borrow and somewhat bastardise one of Gilles
Deleuze’s favoured analogies – make a useful analogy in conceptualising this.
Traffic – an essentially abstract conception of vehicles in transit – between the
nodes of the network – houses, suburbs, cities – behaves in a similar way to
information. Each car represents a single packet of information, while the traffic
itself can be seen as a set of flows within a defined system. Within the network,
this traffic is restricted to clearly-defined travel pathways – the roads. While new
roads can and will be built, traffic is not entirely autonomous – in order to move
between nodes which are not directly connected to one another, cars must find
their way through other nodes. Similarly, information is rarely able to move
directly from one place in a digital network to another. Rather, it must often
travel via multiple other nodes within the network.
This mediation is crucial to our understanding of information’s behaviour
within the network. It is easy to be lulled into conceptualising information as
travelling instantly and without mediation from one point to another – indeed,

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with the transmission speeds of which modern communication technologies are
capable, it does appear to be so. However, it is important to understand that this
is not the case – data is mediated through, and by, its transfer.
Friedrich Kittler argues that technological mediation has a significant effect
on information. He explains the process of data transmission or transfer thus:
• Firstly there is an information source which selects one message per unit
of time from the either enumerable-discrete or innumerable-continuous
quantity of possible messages.
• Secondly this source supplies one or more transmitters which process the
message via suitable coding into a technical signal (something which is
quite impossible in the discrete case without intermediate data storage).
• Thirdly these transmitters feed a channel which safeguards the
transmission of the signal in space and/or time from physical noise and/or
hostile interference.
• Fourthly these channels lead to one or more receivers which reconstitute
the message from the signal by subjecting it to a decoding algorithm
inverse to that of the transmitter, so that finally,
• Fifthly, the retranslated message arrives at the address of an information
drain
(Kittler, 1996, p. 2)
This process of coding and translation affects data’s behaviour in specific ways.
We see information being “decoupled, in the form of a massless flow of
electromagnetic waves, from communication” (pp. 7-8). This idea is key – by
being translated into limited, finite code, information is made concrete. The
process “mechanizes for the first time in history language itself,” while the
“formal languages” used to construct the codes used to communicate with and
through technology “distort” data (Kittler, 2006, pp. 48-49).
Bernhard Siegert argues along similar lines. He states that “media appear
as code-generating interfaces between the real that cannot be symbolized and
the cultural order” (Siegert, 2007, p. 29). Siegert posits that media constantly
interact with and alter cultural codes. Building from Michel Serres’ notion that the
relationship between information and the “channel” which connects any two
communicating “stations” is more important than the sender-receiver relationship

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(“in Serres’s model of communication it is not the sender-receiver relationship
that is fundamental but that between communication and noise”) Siegert argues
that any deviations in meaning brought about by the channel are a necessary
and inevitable consequence of the mediation of information (pp. 29-30). We can
see these ideas in the simple example of a telephone call. First, the existence of
the medium, the telephone itself, serves to establish a mode of communication
which will interact with the cultural context; second, the physical distance
between the two parties will define the manner of communication; third, the de-
and re-construction of the actual words being spoken, and the way they are
expressed, through the telephone technology will affect the sound reaching the
receiver, giving the medium itself far more influence over the information being
transmitted. Thus the fact that the communication is mediated in some way,
whether it is by context, technology, culture, or otherwise, becomes crucial to
the interpretation and meaning of the information being sent from one “station”
to another.
For both Friedrich Kittler and Bernhard Siegert, communication
technologies are not simply passive conduits for information – they are active in
affecting data’s behaviour and meaning at a number of levels. All information
technologies, because they communicate data in certain ways, do this. The flow
of information must always be thought of as subject to conscious or unconscious
mediation by whatever human and technological actors are involved.
**************
Next we must synthesise a model through which to conceptualise power
relations in the online sphere. A four-layered model, combining Michel Foucault’s
three-tiered theorisation of control and Alexander Galloway’s protocological
control thesis, will serve as the basis for this.

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According to Michel Foucault, there are three layers in the exercise of
control: the sovereign, the disciplinary, and the biopolitical. The first of these is
the most basic. Foucault says that it:
consists in laying down a law and fixing a punishment for the person who
breaks it, which is the system of the legal code with a binary division
between the permitted and the prohibited, and a coupling, comprising the
code, between a type of prohibited action and a type of punishment.
(Foucault, 2007, p. 5)
In this case the punishment is an end in itself – it shares a binary relationship
with the offence. The goal here is to provide a direct disincentive for crimes that,
directly or indirectly, undermine a ruler or regime, by fostering a direct link
between crime and consequence. In relation to 18th
Century France’s approach
to crime, Foucault says, “in every crime there was a crimen maiestatis” – a
“crime against his/her majesty”. A crime was seen as being committed against
society, and therefore against the ruler. Punishment, therefore, was retribution.
This is the key feature of sovereign power – it is a product of the sovereign
desire to maintain power over a population, the result of a “king’s desire to
assert his power.” Highly visible public punishments – like execution or mutilation
in the France that Foucault writes of, or publicised trials and imprisonments in
the modern day – create a “spectacle of the scaffold,” establishing a clear
connection and causality between crime and punishment (Foucault, 1977, pp.
53-55). The purpose of this is twofold – the punishment functions both as the
state’s vengeance upon the criminal, as well as a means of discouraging others
from also committing crimes. It is not enough to merely punish the perpetrator –
the direct path from act to consequence must be extremely clear for the state’s
citizens. This binary relationship between crime and punishment is crucial here –
the latter is the exercise of the sovereign’s control over the body of the subject.
In constructing the act of crime and the reaction of punishment as fundamental

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elements of the same phenomenon, the disincentive for crime becomes self-
evident.
The second layer of Foucault’s theorisation, which operates beneath, and
in conjunction with, the above, relates to surveillance and the consequent
internalisation of discipline. Foucault refers to this as the “disciplinary
mechanism” (Foucault, 2007, p. 5). Beyond making the spectacle of punishment
a disincentive for antisocial or criminal behaviour, this mechanism causes
discipline to be internalised through a combination of surveillance and penal
practice. “A series of supervisions, checks, inspections and varied controls” make
crime prevention a more efficient process, while “a practice like incarceration
with a series of exercises and a work of transformation on the guilty person”
prevent recidivism, as well as teaching and internalising ‘correct’ behaviours (p.
4). Foucault’s best-known example of the manifestation of this idea lies in
Jeremy Bentham’s panopticon prison layout. Bentham’s design effectively
isolated each inmate of a prison, removing their ability to communicate with one
another, in positions where centrally located guards could watch them without
themselves being seen (see Fig 2.1).
Fig.2.1. Bentham’s plan for the Panopticon. (Bentham, 1843)

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The design created uncertainty for the inmates – they would not be able to know
if they were being watched, but they could be at any given moment. This caused
them to internalise the prison’s discipline. Foucault describes this is serving to
“induce in the inmate a state of conscious and permanent visibility that assures
the automatic functioning of power” (pp. 200-202). We can use this to assist in
conceptualising surveillance in a broader sense. In a society where any public
action can – ‘can’ being the key word here, as opposed to the more definite ‘is’ –
be tracked by authorities, the direct exercise of control should not be necessary
as often. The surveillance society operates differently to the “enclosed institution
… turned inwards towards negative functions arresting evil.” Rather, it is
produced by a “design of subtle coercion,” a “lighter, more rapid … discipline-
mechanism” (p. 209). We see this in the modern day in patterns of online
surveillance, established with the broad intent of reducing antisocial or criminal
behaviour. A major example of this has been China’s Golden Shield surveillance
network – by monitoring mail, instant messaging and general web use, as well as
utilising IP – Internet Protocol – address data to geographically locate users,
before discipline is enacted (Gutmann, 2010). This marries to Foucault’s thesis of
the disciplinary society, wherein the conceptual foundation for authorities’ actions
“is one not of spectacle, but of surveillance” (Foucault, 1977, p. 217).
The final layer in Foucault’s conceptualisation of control is the exercise of
biopolitical power. This is less direct than the previously addressed forms. It finds
its basis in the structures present in our lives, whether they be physical, cultural,
political or social. Gilles Deleuze uses the highway as a metaphor to distinguish
this from the disciplinary control outlined above:
(It) is not discipline. You do not confine people with a highway. But by
making highways, you multiply the means of control. I am not saying this is
the only aim of highways, but people can travel infinitely and ‘freely’
without being confined while being perfectly controlled. That is our future.
(Deleuze, 2007, p. 322)

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This form of control situates the path of least resistance, in any given context, in
the same place as an ideal behavioural norm – the easiest and most obvious
option for most people is the same as, or similar to, what those seeking to assert
control see as desirable. The design of Deleuze’s freeway, for example, makes it
possible to engage in anti-normative behaviour – that is, to disobey the rules and
conventions that govern road use. However, there is little reason to do so, as it
would make the experience more dangerous and less efficient. According to
Foucault’s conceptualisation, these biopolitical mechanisms of control do not
impose behavioural norms by force, nor do they aggressively seek to cancel out
behaviours that run counter to the norm. Rather, they simply make normative
action more attractive and efficient, thus progressively cancelling the others out.
“They involve the delimitation of phenomena within acceptable limits, rather than
the imposition of a law that says no to them” (Foucault, 2007, p. 66) – the
freeway provides travellers with a highly efficient means by which to reach point
B from point A, but which is dependent on a well-defined set of behaviours,
which a vast majority of drivers must adhere to, in order to properly function.
The basis of this form of power lies in the management of statistics and
probabilities – to keep criminal or antisocial behaviour “within socially and
economically acceptable limits and around an average that will be considered as
optimal for a given social functioning” (p. 5). This is not a concrete, totalising
mechanism of control. Rather, it looks to establish sets of behavioural norms in
order to passively shape, rather than change by force, the way a society
functions. In a real-world communication context, we see this in activities such
as letter writing, where a certain set of behavioural norms, which are rarely
explicitly delineated, provide a framework within which information can pass
from one party to another in a relatively efficient way. These norms may be as
simple as using the same language or dialect, or utilising standard grammatical
constructions in order for the communication to be as clear as is possible. The
key here is that expression is not impossible without subscription to these norms
– they simply make it easier and more efficient.

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Alexander Galloway and Eugene Thacker’s work on network protocol adds
another layer to Foucault’s theorisation of power and control. They define
protocol as “a totalizing control apparatus that guides both the technical and
political formation of computer networks, biological systems, and other media.
Put simply, protocols are all the conventional rules and standards that govern
relationships within networks” (Galloway & Thacker, 2004, p. 8). Manuel Castells
sees it similarly, referring to protocol as defining “rules of performance” for a
given network (Castells, 2009, p. 20). However, this only provides a basic
understanding of the function of protocol. Without it, a network can, quite
simply, not function – it provides the methods by which data can be transferred
while simultaneously establishing limits on the ways this can occur. Unlike the
previously mentioned mechanisms of control, protocol is non-negotiable –
without strict adherence to it, information cannot travel between nodes of a
given network. As argued by Vilém Flusser of the limitations of photographic
technology, this creates a system that is entirely incapable of randomness
(Flusser, 2000). Similarly, Sean Cubitt argues of strictly protocological
technologies, using the screen as an example, that they allow us to “produce
new kinds of cultural content, new user-generated innovation without
challenging the overall logic of the status quo” (Cubitt, 2009). Unpredictable
behaviour is caused solely by human input. Even this randomness, however, is
strictly moderated by the limitations established by the system’s protocol. While
the technology may allow for significant freedom in many facets of its use, its
must also have necessary, established limitations. Indeed, one can argue that
protocol’s defining feature is the constant, unavoidable tension between its
capacity to liberate and its ability to constrict behaviour.
In summary, and to borrow and elaborate upon Cubitt’s extension of Gilles
Deleuze’s metaphor of the freeway, if you drive down the wrong side of the
road, sovereign power will take your car and driver’s licence, and destroy both;
surveillance will make you feel guilty; biopolitical control will allow for the
probability that some small proportion of the population will drive down the

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wrong side, but that it can be kept within a certain range of tolerance; and
protocological control will mean that the car is not able to travel in the wrong
direction on the road (Cubitt, personal communication, May 2 2012).
The following chapters constitute an attempt to reconcile these theories
regarding power and control with the above conceptualisations of the behaviour
of information and data within digital networks, within a context provided by
Twitter.

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An initial Foucauldian assessment
The first step in investigating the mechanisms of power present in Twitter is to
analyse the website in relation to our four-layered model of social power and
control. By assessing how protocological and biopolitical factors affect the
website’s use and moderation, we can in turn see how disciplinary and sovereign
elements of power can be exercised.
Protocological elements necessarily force Twitter to be used in a certain
set of ways. Perhaps the most noteworthy of these is the imposition of a 140-
character length limit on all tweets. This has several, perhaps self-evident,
outcomes. First, it removes some of the user’s agency – with a word limit comes
a restriction of the range of expression available to the user. It forces people to
utilise language more economically than would otherwise be necessary –
expansive conversation is made close to impossible. Secondly, it limits users to
one simple topic per tweet – it is close to impossible, within 140 characters, to
communicate multiple ideas, or, indeed, an individual complex thought. Instead,
users are forced to either post across several tweets, or to sacrifice nuance in
favour of brevity. The consequence of this is that a form of Twitter-specific
meta-language has developed. While this occurred, and continues, more or less
organically (hashtags.org, 2012), it greatly increases the site’s facility for
biopolitical management of information – if one can predict the ways in which
information is communicated, it becomes much easier to manage and control its
flow. Thus this meta-language becomes important to the website’s continuing
utility. Without a consistent mode of expression throughout the site, Twitter’s
continuing facility for broad-ranging, communal interaction is essentially crippled
– as a site reliant on user-created content, normative communication behaviours
are a necessary means for the information travelling through and beyond the
website to be of continuing use.
The site largely relies on users subscribing to various linguistic and
behavioural norms, not only so that it functions properly, but also so that the

18. 18
users experience it in what the site’s designers and owners see as the ideal way
– that is, as a network which enables users to communicate openly and freely
with one another. Twitter’s many strongly established conventions around the
structure and composition of tweets can serve to illustrate this. A tweet can
include a ‘hashtag’ – the use of the ‘#’ key to tag tweets to topics of discussion
within the websites and make them more searchable – a ‘mention,’ or ‘@-tag’ of
another user, which consists of an ‘@’ followed by their username, a retweet, a
way of quoting another user’s tweet using the acronym ‘RT,’ and hyperlinks to
other sites, often using URL-shortening services such as bit.ly and tinyurl.com to
keep the tweet within the character limit. These conventions serve to normalise
the ways in which users communicate within the site. Given that the site’s raison
d’être is to “connect users to the latest stories, ideas, opinions and news”
(Orlean, 2010), and that these conversational elements are the standard means
for users to achieve this kind of connection, this behavioural normalisation within
the site is absolutely necessary to Twitter’s smooth operation. We can therefore
think of these conventions as comprising the site’s means of biopolitical control.
While at a technical, protocological level they are not strictly necessary in order
to use the website, they nonetheless make it much easier to interact effectively
with the broader Twitter community. Indeed, it is close to impossible to interact
effectively within the site without utilising its meta-language or otherwise
interacting in a normative fashion. This is reminiscent of Deleuze’s metaphor of
the freeway – much as most cars on the road abide by a largely unwritten code,
Twitter users tend toward these conversational norms. This biopolitically-
enforced normativity can occur in a relatively politically neutral manner –
Twitter’s inbuilt control mechanisms serve to establish and maintain behavioural
norms and allow for ease of use within the website. We can draw two things
from this: first, that in a broad sense, normative behaviour is, by its very nature,
relatively easy to predict and thus easy to track and moderate; and second, as
we will see, the consequence of Twitter’s particular normative behaviours is that
tracking of individual and collective data is very simple.

19. 19
Hashtags and @-tags, in particular, highlight this normalisation of
behaviour. While they are far from compulsory features of a tweet, their
extensive use makes connecting with topics, conversations and other users far
easier for anyone on the site. Their primary function is to link tweets to topics,
conversations, users, and each other. In doing so they form a dense network of
linked tweets, topics and users within the website – they work to organise the
data within the site. Of particular importance here is the fact that the
organisational element in each post – the tag or tags – is one of the basic,
normative elements of Twitter use. Thus posts effectively organise themselves
within the site. This is a key element to consider when assessing the ways this
information can be, and is, used. If one of the fundamental, normative means of
interaction within the site carries a primarily organisational function, it must
necessarily have a large impact on the mechanisms of power associated with the
site.
This self-organising aspect of the data within Twitter is crucial. The highly
linked nature of tweets has strong implications for the ways in which the data
therein can be utilised – and, indeed serves to generate more information about
the connections and relations present within the network. It demonstrates neatly
the ways in which online behaviour, while ostensibly organic and unpredictable in
nature, is simple to monitor and mine for information. As conversations on
Twitter organise themselves according to key words, phrases, and users (or user
combinations), they are extremely easy to filter and search. Tweets are digitally
connected to the issues, users and linguistic tics that they relate to. These
connections are indelible – they form a permanent part of the ever-growing
social, cultural and historic architecture of Twitter. Any and every association on
Twitter, from a simple impression – the appearance of a tweet on an active
account’s home-page feed – to a retweet or direct response, becomes a
permanent part of the site’s data structure. Essentially, this means that every
interaction on the website, no matter how momentary or passive, contributes to
creating an ever-densifying network of digital links, and a perpetually growing

20. 20
digital history within the site. The result of this is that users become digitally
embedded in a hypertextual web, permanently connected to any and every topic,
user and expression they have posted or seen. The overriding consequence of
this is that not only does monitoring of individual and collective Twitter
behaviour, whether by authorities, marketers, criminals or other external forces,
become very simple to conduct, but vast amounts of information about both
individuals and groups can be drawn from the site.
This creates two significant issues regarding users’ independence of action
and expression. The first of these is that authorities can now treat Twitter as a
means by which surveillance can be conducted on individuals. This has been
increasingly in evidence in the last three years, as governments seek to gain
some level of control over online expression and information distribution. A
number of incidents have demonstrated authorities’ willingness to pursue legal
action against users, based on information taken from the site. Beginning in April
2009, Daniel Knight Hayden, an Oklahoma resident was arrested after posting
threatening messages on the site (Johnson, 2009), while in May of the same
year a Guatemalan man, Jean Anleu Fernandez, was arrested for “inciting
financial panic” (Carroll, 2009). In early 2010 an Englishman, Paul Chambers,
was arrested on terrorism-related charges after making a joke on the site about
blowing up Robin Hood Airport in Nottingham (Hughes & Walsh, 2010) (Fogg,
2010). Similarly, in early 2012 a 21-year-old Welsh student, Liam Stacey, who
posted several racist comments about a soccer player, was charged with racially
aggravated public disorder and jailed for 56 days (Press Association, 2012)
(Press Association, 2012a). Taken collectively, these events can be seen as
exemplifying elements of the sovereign and surveillance approaches to power –
we see the surveillance aspect of disciplinary society, combined with the public
spectacle of punishment.
In each case, Twitter activity was tracked according to traffic relating to
certain issues, key words or users – once the offending posts were made on the
site, police were able to easily find them, track the users responsible and enable

21. 21
the courts to discipline them accordingly. In a Foucauldian sense, this served the
dual purpose of exacting some form of retribution upon the perpetrator of the
antisocial behaviour as well as establishing the fact that Twitter, being a public
forum, is easily surveilled – the intention here being to lead users of the site to
internalise the discipline being practiced against a small minority of them. Thus
we see a social and cultural, rather than physical and corporal, equivalent of the
Foucauldian idea of the ‘spectacle’ of public punishment. With the authorities’
ability to visibly discipline Twitter users engaging antisocial behaviour comes a
reminder of the non-abstract nature of online behaviour – users are forced to
realise and internalise the knowledge that what they do and say online has a
genuine impact on what will in turn occur offline. These elements mirror
Foucault’s theorisation of the outer two layers of power’s manifestation –
sovereign power and the disciplinary mechanism.
This leads us to the second problematic area regarding users’ relationship
with Twitter – the ownership and control of collective data. In September 2012
Twitter was forced by a US court to hand over archived data regarding an
Occupy Wall Street protestor, Malcolm Harris (Associated Press, 2012) (Kary,
2012), while at roughly the same time, the British government viewed a
proposed parliamentary bill with provisions to record all internet use, including
that of Twitter, within the country (Halliday, 2012). These events further suggest
an institutionalised approach to online surveillance and, at a governmental level,
an understanding of the sheer depth of data available on such a site. This
suggests a shift from a solely disciplinary approach toward the additional use of
data to analyse and utilise online behaviour at a biopolitical level – usage data
from a site such as this can facilitate analysis of an enormous breadth of trends,
discussions and other relevant indicators of sentiment (Filloux, 2011). Advertisers
and corporate actors can utilise the site in similar ways. While information about
their use of data from Twitter is scarce, it has the potential to be used in a
similar way to that from Google. Both sites have enormous potential for their
constituent data to be used in similar ways, due to their massively linked nature.

22. 22
Twitter utilises the connections between users, topics and keywords, while
Google uses those between individual webpages (Rogers, 2002). This means that
we can draw significant conclusions from the latter about the way the former can
be used by external actors. Google’s data is useful to advertisers and marketers
at an essentially biopolitical level. Broadly speaking, it provides vast amounts of
information about trends – much as authorities can use the site to inform them
about criminal or antisocial behaviours and trends, commercial organisations,
too, can use the data for their own market research. The individual and collective
implications of this data use, both by government and corporate actors, lie in the
potential for such a densely linked and well-organised data set to be mined for
pertinent information. Such data, when analysed in total isolation from the users
themselves, contributes to a significant power imbalance – governmental and
corporate actors are able to exploit the information placed in the site by its
users, inevitably bestowing a clear advantage upon them.
Organisation of data, while useful for users, naturally affects patterns of
control. Any organisational paradigm must necessarily have a parallel paradigm
of power associated with it. In this case, we see several key ways in which actors
other than individual users can be seen as exercising control over data on
Twitter. Here it is evident that, as far as control over the data they generate is
concerned, users are limited in the power they exercise through the site. Rather,
external actors, whether governmental, corporate or otherwise, hold the balance
of power. There are two main issues leading to this. First, because surveillance is
so simple to execute on the site, given its organically formed self-organisation,
authorities are able to exercise both sovereign and disciplinary power, to utilise
the Foucauldian wording, directly over users. Second, external actors are able to
utilise the vast quantities of data on the site, allowing them to exercise an
indirect form of power – the use of biopolitical data, independent of its subjects.
The ability to tap into such densely linked and well-organised sets of data can
only put the balance of power in the hands of those external influences who
have access to, and can therefore exploit, this information.

23. 23
The conversation
At the core of Twitter’s appeal is the idea of ‘the conversation’ – the flexible,
apparently amorphous “blank canvas” that allows users to connect with topics,
issues and other users (Addington 2012). As the nominal focal point of the
website, an understanding of these conversations is vital to our comprehension
of the network in a broader sense. In order to gain such an understanding, we
must answer several key questions: how does a conversation form and grow on
Twitter; what does this tell us about the flows of information within the site; and
how do these factors contribute to our understanding of Twitter’s power
structures?
The first of these questions is fundamentally a structural one: how does
the architecture of Twitter mediate communication and cause its users to interact
with one another? We will assess this by establishing and analysing a general
model for typical conversation on the site, separated into a number of phases1
.
This can be described as a broadcast model.
Phase 1: Broadcast
An initial tweet is posted on the site, often using a hashtag or key phrase
to increase the potential pool of impressions, or link the tweet to an
existing issue or conversation. An @-tag can be used to link the tweet to a
conversation surrounding an existing user.
1
It should be noted at this point that this is not intended to be a perfect model for all
Twitter conversations. Rather, it simply seeks to demonstrate the different ways in
which a conversation can develop.

24. 24
Fig 5.1 – (Twitter.com 2012) 2
In this case we see a user connecting with a topic that was generating
significant traffic at that point in time. The user, because he has
approximately 40,000 followers, and thus an ability to make a large
number of impressions with each tweet, did not need to include hashtags
to create interest and discussion here.
Phase 2: Acceleration/Splintering
An initial group of users respond to the original tweet, some of whom will
use more hashtags or @-tags to extend the conversation’s reach, at which
point several sub-conversations (or ‘splinter threads’) form. As more
people respond, the virtual footprint of the conversation becomes much
bigger, creating more impressions, which leads increasing numbers of
people to interact with the topic, if not the initial tweeter.
Fig 5.2 (ibid.)
2
All images here are stem from one post. See Appendix for expanded conversation.

25. 25
Fig 5.3 (ibid.)
Fig 5.4 (ibid.)
Here we see the first interaction following the initial tweet. One user
responds, before the first tweeter uses an @-tag to draw in another user.
This broadens the conversation by directly addressing a user, thus linking
him to the conversation, as well as increasing the number of potential
impressions.
Phase 3: Densification
At this point, major splinter threads consolidate to become self-contained
conversations. Their structure mirrors that of the broader conversation,
thus lending the overall conversation a self-similar structure. Graphically
represented, this would give the conversation a fractal appearance.
Fig 5.5 (ibid.)

26. 26
Fig 5.6 (ibid.)
Fig 5.7 (ibid.)
Here we see a splinter from the initial conversation consolidating. In Fig
5.5 a user replies to the tweet in Fig 5.4. Fig 5.6 and Fig 5.7 are separate
replies to this – here, as more users are tagged into the conversation,
thus causing more to see it and potentially become involved, it splits along
conceptual lines. In this case, from the initial tweet regarding the result of
an international soccer match, we have seen a conversational thread
regarding the influence of money in the Australian game further splinter.
Phase 4: Wind-down
After an initial flurry of activity, the number of people involved in the
conversation tails off. Some splinter threads continue to grow and further
split, but the initial tweeter’s involvement is by this point extremely
limited.

27. 27
Phase 5: After-shocks
Latecomers to the conversation may see and respond to the initial tweet
after the majority of traffic has ceased. These tweets may instigate further
discussion, but their impact on the main body of the conversation is,
obviously, limited.
Among the defining elements of this model is its self-similar nature. The
threads splintering off after the initial wave of responses to the first tweet each
follow the same structural patterns as the broader conversation, giving it a
fractal-like structure. This can, in theory, continue ad infinitum – this pattern of
splintering, acceleration, and densification can repeat for as long as there are
Twitter users with an interest in the conversation’s subject matter. We can use a
river system as an analogy to this type of conversation – with the original,
central thread of the conversation represented by the main body of the river, we
can think of the splinter threads as smaller rivers flowing away from the main
stem, their splinters as yet smaller creeks, and so on. Each of the sub- (and sub-
sub-) conversations operate in parallel and largely independent of each other,
but still follow these broadly similar patterns and flows. As a consequence of this
conversations can be somewhat predictable – they will inevitably grow and
spread in certain ways. As we saw in Chapter 3, predictable behaviours are
simple to monitor, and therefore relatively easy to exercise control over.
Also of interest is the impact of a conversation’s footprint on the way it
progresses. The potential for these interactions’ growth to accelerate
dramatically is enormous. As the conversation continues, the number of
impressions its constituent posts are making increases exponentially, thus in turn
increasing the potential for others to become involved. This contributes greatly
to the flexibility and fluidity of these interactions – there is no predetermined
group of actors in a given conversation. Rather, there is a small number – one or

28. 28
more – of initial participants, and the scope for an almost unlimited number of
others to become involved further on in its course. This means that, beyond a
very basic structural level, there is enormous potential in any given conversation
for it to go in any direction, and have a large variety of information added to it.
Rather than the technology channelling the subject matter of a conversation in
any given direction, it serves to expose it to the full range of external influences.
Continuing with our previous metaphor of the conversational river, we can think
of these potential influences as tributaries flowing into the river, thereby
increasing and accelerating its flow.
However, this fast-moving nature is not conducive to profound argument
or considered debate. There is a vastly reduced requirement for focus on a single
issue, or train of thought, within a conversation. Because a variety of users can
be involved in multiple parallel interactions regarding related topics at once,
individual posts compete for users’ interest. This can result in users placing an
emphasis on wilful contrariness, eloquence or wit instead of thoughtfulness –
Twitter is a noisy forum, where only those who shout loudest can be heard. We
can see an example of this in Fig 5.5. In this case the tweeter @-tags the
accounts of a number of Australian ex-professional soccer players in a post
disparaging their ability in the sport. This serves not only to bring those
individual users into the conversation, but also to broaden the footprint of the
conversation and cause other users to respond. As a comment with the aim of
monopolising attention and instigating responses, which it achieves on both
counts, this demonstrates the weakness of the narrow nature of Twitter posts –
by limiting the range of expression possible, the site creates a situation where
the attention-grabbing potential of a post becomes a priority. This subtly
channels conversation toward bombast, perhaps at the expense of profundity.
As far as the mechanisms of information control are concerned, these
conversational structures offer something vastly different to the rest of this
study. They are flexible and context-dependent, as well as being mostly non-
hierarchical (although we will see in the next chapter how all interactions on the

29. 29
website occur within a certain hierarchy). There is a certain democratic logic to
the progression of the conversations – posts of interest attract replies and thus
spawn larger numbers of responses than those with irrelevant or uninteresting
content. In this sense, this can be considered a genuinely egalitarian aspect of
the site – a post’s enduring impact is dependent on how many people see and
want to respond to it. This reliance on impressions, however, contributes to a
notable imbalance – those with the most people following their account will
inevitably have the largest potential audience for any conversation, and can
therefore affect the direction of any given interaction more than users with fewer
followers. Here we see a clear tension. While we certainly see the democratising,
egalitarian influence of almost completely open access to conversations, there is
also a clear potential for those with the greatest social footprint on the website
to exercise some significant level of control over the conversations occurring. It
is tempting, therefore, to treat the empowerment of users to dictate the course
of conversations as somewhat illusory. However, to do this would be to discount
the potential of the sheer number of users who can become involved in any
interaction on Twitter. The most important aspect of this open conversational
model is that it immediately takes control over the course of a given
conversation out of the hands of its instigator – their initial tweet may loosely
define the topic of conversation, but the conversation’s progress from that point
on is governed by popular sentiment and response. As we will see in the next
chapter, though, the hierarchy of popularity does, indeed, play a significant part
in dictating the flow of information through the site.
Twitter’s conversational structure has several implications in terms of the
power balance it serves to establish. We have seen two features that define
Twitter interactions. While on one hand we have a relatively rigid framework, or
set of frameworks, within which a conversation will take place, on the other we
see an open conversational tool that allows for large, almost organically growing
audiences and bases for participation. It is this duality, liberation and limitation
acting in parallel, which defines much online interaction. The tension between

30. 30
the ability of influential actors with large followings and the potential for other
users to influence the flow of information creates a complex structural power
dynamic – we see hegemony over, and democratisation of, information flows
occurring simultaneously.

31. 31
Toward a social structure of Twitter
Claims to universality have their sinister underbellies
(Cubitt, 1998, p. 149)
The defining factor in any online power structure lies in how information is
controlled. An understanding of how Twitter’s structures affect its behaviour, and
therefore facilitate elements of control, can provide us with a model for how this
occurs. A useful starting point here is Friedrich Kittler’s 5-stage model for how
technologies mediate, and thus affect the meaning of information. Applying this
to Twitter, or, more precisely, an individual tweet, gives us a sense of how the
medium tends to affect information in a certain set of ways.
• Firstly there is an information source which selects one message per unit of
time from the either enumerable-discrete or innumerable-continuous
quantity of possible messages
• Secondly this source supplies one or more transmitters which process the
message via suitable coding into a technical signal (something which is
quite impossible in the discrete case without intermediate data storage). .
(Kittler, 1996, p. 2)
During these first two stages, the initial protocological elements detailed in
Chapter 3 affect the tweet. The tweet is broken down into its component data
packets, in order to be transmitted through the network, thus being “decoupled,
in the form of a massless flow of electromagnetic waves, from communication”
(Kittler 1996: 7-8).
• Thirdly these transmitters feed a channel which safeguards the transmission
of the signal in space and/or time from physical noise and/or hostile
interference.
• Fourthly these channels lead to one or more receivers which reconstitute
the message from the signal by subjecting it to a decoding algorithm
inverse to that of the transmitter, so that finally,
(Kittler, 1996, p. 2)

32. 32
These two intermediate stages function as the means of transport for the
tweet, which is now in code form. This is where the most “interference” – that is,
the greatest mediated effect on the data – occurs. In Twitter’s case, this takes
the form of @-tags and hashtags being automatically converted to hyperlinks,
and the tweet being linked to the user’s account. This linking element is crucial –
as we have seen, the level of connection between posts has a significant impact
on the data architecture of the website and its community.
• Fifthly, the retranslated message arrives at the address of an information
drain
(Kittler, 1996, p. 2)
Finally, the tweet reaches the last phase of its broadcast, and present,
having been mediated by the network and the website, on the feeds of all of the
initial tweeter’s followers. This is the end point of this individual tweet’s progress
through the network – if it is retweeted or quoted, the information within the
tweet will be mediated again, as per Kittler’s model.
According to this model, among the key determinants of the meaning of a
piece of communication is the process of mediation itself. This links neatly with
Bernhard Siegert’s work on cultural techniques, where he argues that “media
appear as code-generating interfaces between the real that cannot be
symbolized and the cultural order” (Siegert, 2007, p. 29). The medium of
transmitting information has a necessary effect on the form that information
must take. In the case of analogue telephony, for example, we see that the
medium adds context and meaning to any interaction mediated therein – the
telephone situates the people participating in a conversation in a limited range of
physical locations and contexts, and limits their modes of expression and
comprehension to simple auditory or verbal cues. The medium of communication
here has a significant impact on the flows of information – it defines the actors in
an interaction, as well as the means that they can use to express themselves. In

33. 33
any technologically mediated interaction, the data flows are inherently restricted.
Any communication medium will have functional limitations in terms of the range
and type of expression it allows, as well as the context in which it can be used.
Indeed, these limitations are often among the defining factors of a given medium
– in the case of Twitter, for example, it is its basis in simple textual expression
that differentiates it from other forms of communication. Data flows within the
site are, from a literal, coding perspective, relatively uniform and simple – there
is little flexibility in how they can be utilised to transmit information. Given the
restrictions on the breadth of expression through any given medium, the major
conduits through which data can travel take on renewed importance. It follows,
then, that those who exercise most control over these restricted flows have the
greatest potential power over the information within the network. For networked
interactions in particular, the nodes through which the most information flows
must necessarily have the potential to be the site of the greatest exertion of
control.
To assess how this affects power relationships, we must analyse these
factors in relation to Manuel Castells’ theorisation of information as constituting a
series of “streams” or “flows” within a network (Castells, 2009, p. 20). If power
within the network lies with those who hold a monopoly on information flows, as
it clearly does, then we see here the balance resting on the side of those with
the most followers, and therefore the largest potential pool of impressions. Thus
we see a clear social structure emerging within the website, whereby those with
large numbers of followers – the ‘leader’ nodes in the network – control, through
their hegemonic domination of the network itself, the bulk of the information
flowing throughout, and those with much smaller numbers of followers –
‘follower’ nodes in the network – taking on an essentially passive role. This has
echoes of Wayne Hope’s conceptual structure of the global capitalist system.
Hope argues that there are effectively two major economic strata within the
global economy – those who control the flow of capital, and those who don’t,
with the former dominating the market and the latter effectively serving their

34. 34
interests. The result is a “networked global culture of business, politics,
diplomacy, entertainment, and information that ex-excommunicates the poor
wherever they may be” (Hope, 2006, p. 282). This has links to Manuel Castells’
notion of “capitalist perestroika” in the digital age. Castells argues that, in the
post-digital, networked world, “rather than looking for territorial boundaries, we
need to identify the sociospatial networks of power (local, national, global) that,
in their intersection, configure societies” (Castells, 2010, p. 18). Hope and
Castells speak in terms of the global economy, which has been transformed
enormously since the onset of truly globalised information and communication
technologies, but the same concepts can be applied in the context of digital
culture. Globalised ICTs do not simply facilitate instantaneous financial
transactions across borders – they also allow cultural products to travel wider,
and at faster rates, than ever before. According to both Castells and Hope, this
has in turn caused a global socioeconomic restructure, where national borders,
while not entirely relevant, become of increasingly less importance, as resources
become easier to move across and between nations.
The intersection of Siegert’s and Kittler’s, and Hope’s and Castells’
concepts is visible within Twitter – leader nodes control the flow of information
to the followers, with only a passing regard for national boundaries. This can be
visualised in terms of a network, comprising two distinct groups of nodes, one
small and one very large, with high degrees of connection between their
constituent nodes and a less dense set of links between the separate groups.
While Castells’ and Hope’s structures are built upon Marxist-influenced
conceptions of the world, whereby power lies in the control of the flow of
economic capital, the basis for these online structures lies elsewhere. Of course,
economic power must have some influence – as in any media form, those with
the greatest market share tend to be wealthy or well supported. However, in this
case, a form of sociocultural capital, whereby those with the greatest
sociocultural impact – whether due to their fame, social prominence, political

35. 35
influence or otherwise – occupy a position of privilege and trust3
, tends to carry
more weight. This would appear to stand to reason – as Twitter’s social economy
is broadly informational, rather than financial, it simply makes sense that those
with the greatest cultural impact should have the largest following, and therefore
the most potential to reach users.
Indeed, Twitter’s 100 most followed accounts are overwhelmingly users
with a great deal of sociocultural or informational, rather than necessarily
economic, capital. Of those 100, 48 accounts – including 7 of the top 10 – belong
to musicians or figures in the music industry, 27 to television figures, 8 to each
of digital business and sporting figures, four to news organisations, two to each
of writers and political figures, and one to a business person (Twittaholic, 2012).
These users, a vast majority of whom owe their status to their popular cultural
impact, may not hold a great deal of high-cultural cachet, nor are they
necessarily traditional sources of information, like journalists or news
organisations. Rather, they represent a new breed of postmodern conduit for
information – the networked public figure.
These users typically display several key characteristics. They are ‘hyper-
active’ – that is, they not only post regularly, but in an eclectic, sporadically
focused way. Highly active accounts, which interact with a wide range of areas of
conversation, generate more data and impressions within the site, thus gaining
traction due to the simple fact of their large digital footprint. As a result of the
large shadow their presence casts, in terms of both sheer number and breadth of
posts, many of these users have a significant impact on conversations occurring
in a range of areas of the site. These accounts’ use is largely dependent on
connection – the users tend to be highly social, generating and maintaining
connections with their followings. These interactions tend to be somewhat
unequal, though – they typically result in poorly-followed accounts gaining large
3
Note that this differs somewhat from Pierre Bordieu’s notion of “cultural
capital,” which revolved around “cultural knowledge” – or, simply what a person
knows, as opposed to how they are perceived (Barker, 2004, p. 37)

36. 36
numbers of impressions through retweets or replies from those with greater
numbers of followers. Here we see another example of the social inequality
within the website – those with small followings often need to lean on the larger
accounts in order for their posts to gain anything other than a tiny foothold. This
further cements the position and role of the latter group as the active conduits or
distributors of information within the website.
It is important here to remain mindful of the hierarchical nature of all
connections made within Twitter. Information within this type of network tends
to travel through a relatively small group of nodes during the process of
distribution to a mass audience. This structure of information dissemination can
be seen as constituting a postmodern equivalent of traditional media structures.
In both cases, we see a large number of passive receptors of information and a
small group of transmitters – the media organisations or individual Twitter users
themselves. The major difference lies in the number of conduits – on Twitter
there tends to be a greater diversity of sources for information, given the site’s
capacity for following large numbers of accounts. Rather than users receiving
information from a small number of sources – as is the case in most traditional
media (Pew Research Centre, 2011) – users with smaller followings often follow,
and thus potentially receive information from, substantially more accounts than
follow them. However, the highly hierarchical nature of the site negates the
impact of this somewhat – there is still an empowered minority acting as
gatekeeper for most of the information flow on the site. Interestingly, this
structure, despite its presence in the apparently fluid web, isn’t discernibly less
stable than in any other medium. In fact, because of the accumulative, hyper-
social nature of the site, wherein users are far more likely to follow accounts
than un-follow them, the hierarchy within the site is perhaps even more stable
than those in traditional media.
The control over data flows we have seen here puts much of the power
within Twitter in the hands of the relatively few people with high numbers of
followers. Because accounts with large followings are responsible for a large

37. 37
proportion of the impressions made on the site, they hold a near-monopoly on
information flows within the user network. As important conduits for these flows,
the users seen here exercise, consciously or otherwise, a great deal of power
over what information travels through the site. We must, of course, remember
that Twitter does not exist in isolation from other media – it is impossible to
assume that it functions as the sole source of information for any given user.
However, the structures established here provide a guide as to the behaviour of
information within the online sphere. While they may be organised along
different lines to other media, these hierarchies still manipulate, consciously or
otherwise, the flow of information to the majority of users.

38. 38
Conclusions
We live in confusing times.
(Castells, 2010, p. xvii)
While there is little doubt that the Internet has great liberatory potential,
its impact on the mechanisms of power within society must be carefully
questioned. Twitter has provided a useful case study for achieving this. Given its
highly networked, protocological and relatively open nature, it functions as a
neat metaphor for the Internet on a broader scale. We have seen how the
website establishes or maintains the mechanisms of online power in three key
areas: (1) the technical control of networked interaction; (2) the nature of
networked conversation; and (3) social structures within the site. We must,
though, assess how this analysis of Twitter can be related to the wider web.
Data organisation is a key area in assessing these mechanisms of control.
In the case of Twitter, individual users are significantly limited in the control they
are able to exercise over the data they generate. Instead, large, external actors
are afforded significant power over information available within the site. This
happens in two key ways: first, because surveillance is so simple to execute on
the site, given its near-organic self-organisation, authorities are able to exercise
both sovereign and disciplinary power directly over users; second, external
actors are able to utilise the vast quantities of data on the site, allowing them to
exercise an indirect form of power – the use of biopolitical data, independent of
its subjects. The lesson here lies in the digital trail created by networked
interaction. The digital sphere can be seen as being defined by its pathological,
inescapable impulse to link and organise. The structures within which digital
behaviours occur are fundamentally incapable of flexibility – digital networks do
not allow for data to move outside a well-defined set of ways. Because of this,
both surveillance and data mining and manipulation are relatively simple. Data’s
tendency to self-organise and situate itself within a dense web of networked

39. 39
interactions gives the Internet a near-cartographic quality – as seen in Twitter,
information defines itself by its relation to other information, with the effect of
situating it at precise points in digital space. It is important to remain aware of
this, and its implications. Data can be used and exploited for sovereign,
disciplinary and biopolitical ends – while this, in itself, is perhaps inevitable, it is
important to understand how it occurs, and what it means.
Twitter’s conversational structure also has several implications, in terms of
the power balance it serves to establish. There can be two different views of
interactions within the site: first, we see a relatively rigid framework, or set of
frameworks, within which a conversation will take place; second, we have an
open conversational tool that allows for large, almost organically growing
audiences and bases for participation. These views are not necessarily mutually
exclusive. Indeed, there is a sense of duality at play here, with both limitation
and liberation acting in parallel. The tension between the ability of influential
actors with large followings and the potential for other users to influence the
flow of information creates a complex structural power dynamic – we see
hegemony over, and democratisation of, information flows occurring
simultaneously. This appears to be a recurring theme within the Internet. As in
Twitter, we see in the Internet a perpetually repeating duality of freedom and
restriction – a medium that is defined both by its protocological limitations and
its enormous potential for open expression and access. This poses a difficult
conundrum – to find the point at which these two factors become balanced.
Again, the overwhelmingly important factor here is an understanding of the
issues presented by web use. An adequate comprehension of the fundamental
restrictions built into all technologies, not just those designed for communication,
is crucial in order to fully appreciate and exploit the liberation they can afford us.
Twitter’s social structures provide another example of the ways in which
the website affects power relationships. The ability to control flows of
information shifts the balance of power within the website toward the relatively
few people with high numbers of followers. Because accounts with large

40. 40
followings are responsible for a large proportion of the impressions made on the
site, they hold a near-monopoly on information flows within the user network. As
important conduits for these flows, the users seen here exercise, consciously or
otherwise, a great deal of power over what information travels through the site.
The structures established here provide a guide as to the behaviour of
information within the online sphere. Given the highly structuralised nature of
the web, the path that data takes to reach individual users is of extreme
importance. In the web’s social, cultural and informational economy, the control
and dissemination of data becomes of significant interest in assessing the
workings of power. Put simply: he who controls information controls the
Internet.
Ultimately, what is vital here is that, as users, we approach the Internet
critically. It is not a politically neutral instrument – its structures naturally cause
certain types of power relations to come into being, and inherently favour
particular actors. The Internet, in essence, functions as one of Deleuze’s
“multipliers of control” – people can “travel infinitely and ‘freely’ without being
confined while being perfectly controlled” (Deleuze, 2007). While it allows its
users a great deal of freedom, it also provides a multitude of additional means
for external forces to manipulate, control, and generally exert power over them.
In a constantly, inevitably changing and ever more confusing world, one
constant is the need to understand how we communicate – how we interact with
society and how it interacts with us. The exercise of power and control, while not
necessarily a negative feature of our, or any, society, is inevitable. To
comprehend the mechanisms of power, and to critically assess them, though, is
to grasp the basic forces that govern our behaviours. Understanding these
forces, above all else, is crucial to comprehending the world in which we live.

41. 41
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