Political Economy of Tracking Technology

{The following is a research paper which I submitted for one of my courses at Swansea University}

Digital Globe

Binary code on a surface of a planet
{Photo source}

Introduction

In the digital age, one may think the rapid development of technologies brings greater freedom as people can access and possess new technologies anywhere and at any time. However, technologies have also made it easier to impose more control over societies (Galloway 2004: 3). Code and software are integrated in digital technologies which we use daily without realizing the amount of data collected about our activities (Berry 2011: 1). Delueze (1992: 4) argues that after World War II, the ‘societies of control’ have taken over what Foucault called ‘disciplinary societies’. ‘For Foucault, discipline is an effective means to reduce the body as a political entity as cheaply as possible while maximizing individual ‘utility’ (Foucault in Kim 2004). Hence, it is vital to understand what is hidden by analysing how and why code and software are used to track people’s behaviour to create new forms of surplus value.

In order to understand what the political economy of tracking technology means, it is important to outline some theoretical foundations. Politics and the economy cannot be separated and must be analyzed together. Political economy therefore is ‘a Marxist model of the media which emphasizes the influence and power of owners and advertisers in decision making’ (Marsh 2006: 734). So, the question is who influences netizens[1] and how are their decisions made? According to Marx, whoever has the ‘material force’ (in this case software) in a society is its ‘ruling intellectual force’ (Marx and Engels 1976: 59). Moreover, this intellectual force is increasingly granted broader ‘intellectual property rights’ in order to have control and prevent others from copying its creativity (JISC 2007).

We appear to be heading towards a political problem where extracting the ‘abstract code from objects’ becomes the main concern overtaking the problem of alienating social relations into objects (Galloway and Thacker 2007: 134). Therefore, discussing the political economy of tracking technologies helps in understanding how code is deployed in society. In this paper, I am going to explore the cultural political economy (hereafter CPE) of tracking technologies in which technologies refer to the mechanisms involved in the governance of conduct and in the production of hegemony (Jessop 2010: 342). I will first explore the theoretical background of this approach and its application and implications on tracking technologies. Then, I will focus on two covert and overt tracking technologies, web bugs and lifestreams respectively.

Theoretical background

I want to begin by explaining CPE and following the work of Bob Jessop in defining and describing the aspects of this approach. The CPE is a ‘post-disciplinary approach that adopts the ‘cultural turn’ in economic and political inquiry without neglecting the articulation of semiosis (the intersubjective production of meaning) with the interconnected materialities of economics and politics within wider social formations’ (Jessop 2004: 1). It differs from other cultural turns by its focus on key mechanisms that determine the co-evolution of the semiotic and extra-semiotic aspects of political economy (Jessop 2004: 2). It generally has three theoretical characteristics which make it distinctive. First, it claims that ‘history and institutions matter in economic and political dynamics’; second it ‘highlights the complex relations between meanings and practices’; and third, it ‘combines evolutionary and institutional political economy with the cultural turn’ (Jessop 2004: 3). It also critically assesses the categories and methods of ‘orthodox political economy’ and stresses on ‘the inevitable contextuality and historicity of its claims to knowledge’ (Jessop 2010: 343).

Furthermore, the role of complexity reduction in the CPE approach is an essential condition of ‘going on’ in the world (Jessop 2010: 337). I want to focus on how we, the observers, reduce the complexity of the world we were unwillingly brought into. In order to be active participants, we try to make sense of everything around us. From childhood, we learn and analyse the things we face in our daily lives. However, this meaning making was not given to us on a silver platter; we had to reflect on and explore the environment in order to learn. We try to make sense of the new technological world around us in the same way. For example, if I buy a new device, I do not put it down until I explore what it does and understand its functions.

Another form of complexity reduction is social interactions (Jessop 2010: 338). How we interact in the society and nature reduces the complexity of our world. Nowadays, these social interactions have taken a different turn due to the emergence of social networks. The world has become a large society because of the connections offered through digital technologies and the internet. In spite of the many advantages these connections may bring, the privacy of individuals is threatened by the monitoring of their behaviour.

The above discussed forms of complexity reduction aim to transform a meaningless and unstructured world into a meaningful world to actors; social interactions undergo ‘structuration’ (Jessop 2010: 338). Moreover, Jessop (2010: 339) argues that technologies ‘are important meaning-making instruments deployed by agents to translate specific social construals into social construction and hence to structure social life’. He also explains that the significance of technologies is ‘the consolidation of hegemony and its contestation in the remaking of social relations’ (Jessop 2010: 337).

After giving a brief explanation of the cultural political economy approach, I will determine the base and superstructure in the digital economy that is related to tracking technologies. Williams (1980: 31) argues that the key to cultural analysis is ‘the proposition of the determining base and the determined superstructure’. If we simplify and apply the theory which I believe is more complex in the field of tracking technologies, then we find that website owners and advertisers (or third parties) are the base as they have control over the economy while netizens are the superstructure with their behaviour (or labour) over the internet. I consider the netizens to be the superstructure because superstructure depends on the modes of production in general (Marx and Engels 1976). The modes of production in this case are labour (i.e. behaviour), instruments (i.e. technical devices that connect to the internet), raw material (i.e. the data and statistics collected from netizens’ behaviour) and social relations (especially those on lifestreams) (Marx and Engels 1976). Trackers act as mediators going to and fro between the base and the superstructure. Despite considering trackers to be mediators, they are also an inseparable part of the base.

In addition, capitalism in a Marxist sense exists in the virtual world today. Both advertisers and tracking technologies form the capitalist bourgeoisie as they have the ability to collect data and target netizens, who are the working class, with advertisements to make surplus profits and control their ideology. The difference between the previous capitalism and digital capitalism is that labour of the working class is made to be more fun but with no income. More specifically, the working class is transformed into the product by alienating their intellectual labour into machines (Berry 2011: 40). The ‘discourse of creativity’ is now used to differentiate between the ‘older industrial form of capitalism’ and the newer form that is ‘creative economy’ (Howkins in Berry 2008: 43).  One of the most important elements of the new economy is the ‘human capital’ where not only creativity and skills are included but also intelligence and reviewing of products (Ticoll 2000). By the use of tracking technologies, behaviour marketing has emerged recently which has raised privacy implications (Berry 2012). For example, if you go to Google and start typing, a drop down list of your previous and other most popular searches pops up. The software Google uses enables the company to collect statistical data about everyone using it. This data is used to determine which product or website is to be used when targeting a customer (or netizens).

The ‘shift in Western economies from the production of goods to the production of innovation’ has created the information society (Berry 2008: 43), which invests more on the creativity of individuals to obtain economic growth. Some argue that creativity is the core of modern economies and that it must be ‘democratised’ where we equally must ‘be creative’ and therefore ‘more productive’ (Florida 2004; Berry 2008: 42). Creativity is also connected with the ‘immaterial production or mental labour’ (Berry 2008: 43) which forms the basis of this modern superstructure. Furthermore, this ‘creative economy’ is ‘based on selling novelty, variety and customization’ and has shifted from the ‘consumption of goods to the consumption of experiences’ (Florida quoted in Berry 2008: 75).

Therefore, Smythe’s (1981) ‘audience commodity’ sees the media audience, who are netizens, as commodities and I believe this is the reason for using tracking technologies. This commoditisation of the audience is used by companies in the market and is sold for advertisers to generate income. Furthermore, this new digital economy gives me the impression of being a slave every time I browse websites on the internet. As there are billions of internet users, tracking technologies deal with humans as numbers and statistics, objectifying us, and they use these numbers to know and even predict our behaviours.

As a result, tracking technologies culture remains hegemonic when netizens do not realise they are the commodity of the new economy. In order to receive the available services and benefits from the society, we must surrender part of our personal information. In return, the society must protect the information against any irrelevant uses (Kim 2004: 197). This is done by imposing laws to protect the data collected. There are discussions about the ‘do not track’ flag which notifies users they are being tracked, but it is not respected by most companies as there is still no legal requirement to do so (Berry 2012).

Also, in a report by the Federal Trade Commission in the US in 2000, the commission tried to set up ‘four widely-accepted fair information practices’ which websites that collect data should abide by. First, any website that wants to collect data should give customers or netizens a notice and information about what data they collect, for what purposes, and if they are going to share it with third parties. The websites should also give netizens a choice whether they are willing to share information or not. Moreover, these websites should give access to what information has been collected from individuals giving them the opportunity to delete, correct or review the data. Finally, the websites are required to have clear and reasonable steps that would protect the information collected (FTC 2000: iii). Even though these practices may not be implemented in most websites, I believe that they are essential in forming privacy laws online which are lacking and that we should merge them in our ideology as part of our civil liberties and rights.

Now, after setting the cultural political economy of tracking technologies, it is time to see the performance of these technologies and how they create the digital economy. There are two kinds of tracking technologies. Covert (e.g. web bug, beacons, tags, etc.) are hidden tracking technologies that collect statistical data and are used by the base to form the superstructure’s ideology in an indirect way. The other is overt (e.g. lifestreams) which are used by netizens in public and shape the effect of the ideological formation.

 Web bugs

To begin with, web bugs are best defined as those ‘electronic tags that help websites and advertisers track visitors’ whereabouts in cyberspace’ (Harding, Reed, and Gray 2001: 22). In other words, web bugs are ‘agents’ which collect data and which are embedded in websites in one-pixel frame to check users’ actions (Berry 2012). They are a tool that delivers cookies for third parties (Martin, Wu and Alsaid 2003: 260). ‘Cookies are small pieces of text that servers can set and read from a client computer in order to register its state’ (Mittal quoted in Berry 2012). They cannot be seen and sometimes anti-cookie filters cannot catch them which make it difficult for netizens to know of their existence. It is possible, however, to check for those bugs by viewing the source code of the web page you’re navigating. Then, search for an ‘img’ tag with the attributes width and height equal 1 and the borders equal 0 (Harding, Reed, and Gray 2001: 22) which look like this:

<img src=”website of the web bug’s source” width=1 height=1 border=0>

As history matters in CPE (Jessop 2004: 3), it is important to understand the political economy of code which web bugs are part of. ‘Code costs money and labour to produce’ and it needs ‘continual inputs of energy, maintenance and labour to keep functioning’. It also runs on ‘private computer networks’ which gives their owners more control over the internet (Berry 2011: 61). Consequently, web bugs allow companies to hold different tasks like ‘unique visitor counts, web usage patterns, assessments of the efficacy of ad campaigns, delivery of more relevant offers, and tailoring of web site content’ (Martin, Wu and Alsaid 2003: 260). These bugs, which ‘execute code to secret cookies’ on computers, are essential for behaviour marketing because they send data back to their servers (Berry 2012).

The CPE takes the ‘cultural turn seriously’ by highlighting the complex relations between meaning and practice (Jessop 2004: 3). These complex relations are discussed in terms of three broad evolutionary mechanisms: ‘variation, selection, and retention’ (Campbell in Jessop 2004: 3). This is demonstrated in the effect of web bugs on the new economy. The meaning of web bugs, as explained above, is a line of characters that is embedded in the source code. However, the effect of this line is enormous because of its variable uses by the base. Web bugs can generate the traffic of particular web pages by counting the times they had been viewed (Berry 2012). This helps companies to know whether their websites are visited or not and helps advertisers select the right website for marketing purposes. For example, Google Analytics uses web bugs as a management mechanism to provide websites with statistical data about their users (Google 2012). It is important for the base to know which websites are visited the most by which users in order to use them as advertisement medium to reach more customers and thus create more surplus profits.

Web bugs are also used to create a digital economy. They generate online profiles about netizens by collecting and transferring demographic data or personal information (Martin, Wu and Alsaid 2003: 260). This information is transferred to third parties whether they are authorised or not by the users. Marketing companies mostly use these types of information to form segments for their products which is the reason behind the retention of web bugs. The privacy issue here has been severely ignored as netizens have no choice whether they share their information or not. This highlights Delueze’s (1992: 4) notion of ‘societies of control’.  Additionally, some argue that not all web bugs are threatening the privacy of individuals, but it is hard to determine unless their uses are identified. I consider these web bugs as CCTV cameras installed to our web browsers to monitor us and our behaviour. They sell the data collected from this monitoring to third parties or advertisers in the economy.

Another use of web bugs is to track the preferences of individuals. They add what pages netizens visit during a single session to their online profiles. Moreover, they pass what each person searches for on search engines to internet marketing companies (Martin, Wu and Alsaid 2003: 260) who in their turn use the data to know what the demand in the economy is. Somewhere out there in cyberspace, each person has a unique identity and a profile that represents his personality through the statistics collected about him. Also, when an individual purchases a product online, these web bugs are used to know which advertisement the buyer saw before the purchase (Martin, Wu and Alsaid 2003: 260). This is to pay a percentage in commission to the website that displayed the advertisement and to determine netizens’ preferences in order to target them with similar ads. Sometimes, these web bugs are used to report back the configuration and settings of the internet browser that we use (Martin, Wu and Alsaid 2003:  260). In doing so, websites can determine what kind of content to put on which websites.

The digital economy has become more dependent on web bugs. Companies use the statistics collected by web bugs to produce new products. As these web bugs ‘form part of the dark-net surveillance network’, they change the experience of users on the internet in real-time ‘by attempting to second guess, tempt, direct and nudge behaviour in particular directions’ (Parry in Berry 2012). Even though we think that we browse the internet independently, the use of these web bugs limits our internet experience. For example, Google’s search engine does not give the same results for two different people because its software enables it to know the preferences of each person and what he would likely look for next.

There are sixteen different types of web bugs which Berry (2012) has categorised into four main types and which I will mention with an example of each. The first main type is ‘Advertiser / Marketing Services’ which includes the ‘exchange’ type that provides a ‘marketplace’ to connect ‘advertisers to ad networks and data aggregators’. The second is ‘Analysis / Research Services’ which includes ‘analytics provider’ that provides statistics in order to understand the ‘market effectiveness’ and to segment the audience. ‘Management Platforms’ is the third type which includes ‘agency’ that is the ‘provider of creative and buying services for advertisers’. The final type is the ‘Verification / Privacy Services’ like ‘online privacy’ which offers netizens transparent data on how third parties use their information (Berry 2012).

The question that remains is how much profit companies generate by using the statistics and analytics that are sent by web bugs. While millions, if not billions, of users depend on Google’s searches, the company generates $24 per user. Amazon’s profits per user are much higher than Google’s: it generates $189 (Yarrow in Berry 2012). This demonstrates why large corporations will keep on using web bugs despite any privacy implications that threaten their customers. This also explains how CPE combines the role of institutions in shaping the behaviour economy with the cultural turn (Jessop 2004: 3).

 Lifestreams

The second example of CPE of tracking technologies, which I will explore, is lifestreams. As the cultural turn, emphasised by CPE, focuses on meaning and practices (Jessop 2004: 3), then they should be highlighted. ‘Lifestreams is a software architecture based on a simple data structure, a time-ordered stream of documents, that can be manipulated with a small number of powerful operators to locate, organize, summarize and monitor information’ (Freeman 1997). These self-monitoring technologies, which are also known as the notion of ‘the quantified self’, were introduced to the cyberspace by ‘a collaboration of users and tool makers who share an interest in self knowledge through self-tracking’ (Quantified Self 2012). This has shown a lot of interest by individuals who started constructing their identities by sharing their information on lifestream platforms like blogs, Facebook, and Twitter. These lifestreams are created for us to ‘desire, both to be in it, to follow it, and to participate in it’ (Berry 2011: 143). )

The digital culture that is created by lifestreams offers netizens a variety of practices. For example, blogs are considered ‘electronic diaries’ (Economist 2010). There are millions of blogs on the internet today. Their purposes may differ but the essence is practically the same: to share information. Some blogs have indeed replaced personal diaries giving the authors the chance to share in public. Most blogs consist of written material but other forms of media, like photos and videos, form important elements in some of them.

Facebook has strengthened social relations through its timeline where people share their news, personal photos, and so on. It has become like a virtual society attracting thereby third parties and advertisers. One of the CPE’s features, according to Jessop (2010: 336), is to show ‘the significance of technologies to the consolidation of hegemony and its contestation in the remaking of social relations’. Facebook does not only form a global society, but also tries to impose more control over the superstructure’s relations by forming its creativity in terms of directing it. For example, Facebook asks its users when they log in ‘what’s on your mind?’ which was recently replaced by a range of different questions such as ‘how’s it going, [user’s name]?’ and ‘how are you doing, [user’s name]?’ Users then share a status with their friends where they indirectly answer Facebook’s questions revealing sometimes very personal data.

Another example of a lifestream that attracted millions of users worldwide is Twitter. Like Facebook, Twitter allows users to share status updates limiting them to only 140 characters and thus imposing a kind of control. It has ‘transformed into a real-time stream’ because it encourages ‘the uploading and sharing of photographs, geodata tags, updates on what you are doing and so forth’ (Berry 2011: 163). It is also used as a communication tool where media, organizations and even governments collect data as users share a vast variety of events including those related to politics, cultural or any other public or private events. Of course, its ‘owner’ and the ‘epistemic community’ around him ‘have the capacity to create a form of social contagion effect’ (Berry 2011: 164) imposing thereby their ideology over this social network.

Further, Twitter is like a ‘new urban-ism’ (Borthwick quoted in Berry 2011: 165). It is a ‘distributed memory system, storing huge quantities of information on individuals, organisations and objects more generally’ (Berry 2011: 165). Privacy is not really an issue because most of its users tweet in public. However, the question is ‘who owns these huge data reservoirs and how will this data be used in the future’ (Berry 2011: 166). Institutions, especially governments, use these platforms to manipulate users and this type of monitoring raises questions about civil rights and liberties.

CPE emphasises on how mechanisms shape the movement ‘from social construal to social construction’ (Jessop 2010: 336). However, lifestreams make it possible to ‘decentre social structures’ raising the concerns of communities as they trace the ‘impact of computational real-time devices in everyday life’ and ‘capture the informal representations’ (Berry 2011: 164). Moreover, the data collected over the lifestreams ‘can be used to reconstruct knowledge of social and political events in an online real-time context’ (Berry 2011: 164). Some argue that ‘we’re finally in a position where people volunteer information about their specific activities, often their location, who they’re with, what they’re doing, how they feel about what they’re doing, what they’re talking about…we’ve never had data like that before, at least not at that level of granularity’ (Rieland quoted in Berry 2012).

Lifestreams, which are also called life-tracking technologies (Economist 2010), are not only about social networks. There are some technologies that emerged or even websites that help people monitor their medical and health behaviour over the internet. For example, ‘lifestream cholesterol monitor’, which is a handheld test kit, gives patients the opportunity to share their records online and to regulate access by other parties like doctors (Albertson 2000). This, I would argue, is a positive way of using tracking technologies as it may help patients to keep track of their health issues. Another two examples of self-tracking devices are Fitbit and Greengoose, which are basically ‘selling wireless accelerometers that can track a user’s physical activity’ (Economist 2010). These tools may help other patients to know more about other people’s experiences. This shows how the new economy of tracking technologies is growing to reach all aspects of life.

The privacy of netizens is diminishing as a result of lifestreams.  Gibbs (2011) states that

Now we have to recognize the death of our “realtime” or “lifestream” privacy: the freedom to go about our business unobserved and anonymously… lifestream privacy involves behavioural data such as where you go and when, what you look at, and even how you respond; it’s more like a movie of you. Taken to its extreme it also includes who you talk to, telephone and email with, and even what you talk about. A lack of lifestream privacy makes it possible, at the least, for businesses to manipulate you… Similar tracking techniques are now in use in the real world, and the connection of your factual data to your lifestream data on- and offline is what many businesses are trying to do (Gibbs 2011: 34).

The labour and ideology in the superstructure are stirred by those lifestreams giving the base more control over the digital society and societies in general. David Gelernter, author of ‘mirror worlds’, predicts that business models based on streaming will dominate the internet in the near future. In an interview, Gelernter asserts:

All the world’s data will be presented as a “worldstream,” some of it public, most of it proprietary, available only to authorized users. Web browsers will become stream browsers. Users will become comfortably accustomed to tracking and manipulating their digital objects as streams rather than as files in a file system. The stream will become a mirror of the unfolding story of their lives (Jeninks 2011).

As a last point on lifestreams, it is worth noting how the information shared on these public platforms is being indexed. The indexing of lifestreams is considered to be part of constructing the digital society and the production of hegemony. For example, a website called ‘The Profile Engine’ (http://profileengine.com/) has generated user profiles through Facebook stating that ‘Facebook has given approval for [them] to index, search and display public parts of Facebook profiles, pages and groups’ (Profile Engine 2013). Moreover, as Twitter is a more public platform than Facebook, it is possible to find users and see their profiles when using Google search. Twitter has also given all its archive, including every tweet, to the Library of Congress where all future tweets will be archived automatically (Berry 2011: 166).

Conclusion

In this essay, I have undertaken a political economy of trackers. First, I examined the theoretical background, particularly highlighting Jessop’s work on the cultural political economy approach. Then, I discussed two examples of tracking technologies – web bugs and lifestreams – and how they affect the economy creating surplus value. I also pointed out how these technologies dominate the economy and the ideology of societies in order to produce hegemony. I aimed to reduce the complexity of these technologies to transform them into a meaningful world to netizens and to undertake ‘structuration’ of social interactions (Jessop 2010: 338). I considered these technologies as mediators between people’s behaviour and the market stirring the economy in accordance. They also empower institutions to impose more control on individuals’ experiences in the new information society. In conclusion, it is clear that more work is needed in the field of political economy of tracking technologies especially with their continuous development and their integration into the digital world.

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[1] Internet citizens

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