Digital Capitalism

1. The logic of the argument “A is not exploited because the exploitation of B is more violent” disregards how different forms of exploitation are united in an international division of labour, from which transnational corporations benefit. They exploit a diverse range of workers in order to accumulate capital. The production of digital media and data is based on an international division of digital labour, in which we find slave workers extracting minerals, Tayloristic assemblage workers, low-paid software engineers and call centre agents, highly paid and highly stressed software engineers, precarious freelancers, user labour, etc. The notion of the international division of digital labour stresses that digital capital exploits all of these digital workers and that they therefore have a common interest to struggle against capital and to organise across national boundaries in the form of a digital labour union. The notion of digital labour is not limited to the users of targeted-advertising-based social media platforms. Marx stressed the connectedness of diverse forms of labour with the notion of the collective worker. In the international division of digital labour, there is collective digital labour.

Not all digital labour is unpaid and based on advertising. YouTube has introduced YouTube Red in the USA and is also rolling out the same programme in other countries: Members of YouTube Red pay a subscription fee for access to ad-free premium videos (including music, series, and vloggers’ content).

Our new paid membership, YouTube Red, lets members enjoy any video on YouTube without ads while still supporting creators. […] New revenue from YouTube Red membership fees will be distributed to video creators based on how much members watch your content.⁵

YouTube celeb vloggers such as Lilly Singh (who had 11 million followers on her YouTube Channel in January 2017), PewDieDie (53 million), MatPat (8 million), Toby Turner (2 million), and Joey Graceffa (7.5 million)⁶ have produced series and movies for YouTube Red. YouTube stars are a labour aristocracy, who can earn some money from their profiles because they managed to accumulate a large number of subscribers. Whereas there is a small number of labour-aristocratic YouTube-Vloggers, the vast number are proletarianised digital workers, working precariously and struggling to earn a living online. YouTube only enables this YouTube aristocracy to produce premium content that is paid for by YouTube Red subscribers. In this model, YouTube can be seen as a temporary employer of these YouTube celebs that pays them a wage for the creation of specific content. YouTube Red subscribers are consuming audiences paying for access to premium content. With the introduction of YouTube Red, Google has diversified its capital accumulation model. It continues to use targeted advertising as main revenue source and has in addition introduced a subscription service. YouTube is therefore based on two forms of digital labour: (a) Users’ digital labour of watching and creating in the case of advertising sponsored part of the platform; and (b) The YouTube labour aristocracy’s paid labour that creates premium content for YouTube Red.

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5 https://support.google.com/youtube/answer/6306276?hl=en-GB

6 http://uk.businessinsider.com/youtube-red-original-movies-and-shows-2015-10?r=US&IR=T/#youtuber-joeygraceffa-will-star-in-a-new-youtube-murder-mystery-series-10

8.3.2 Digital Alienation

Alienation (Entfremdung) is a term that Marx used for characterising conditions that humans are not in control of and under which they live. Alienation not just signifies an objective structural condition, but also a subjective feeling of dissatisfaction. In discussions about digital labour, there have been different approaches about how to think of alienation in the context of social media.

Mark Andrejevic argues that commercial social media only have an appearance of being non-alienating because they foster play and sociality. But in reality, using them means a form of digital alienation, “a form of the enclosure of the digital commons” (Andrejevic 2012, 84). “Users have little choice over whether this [surveillance] data is generated and little say in how it is used” (Andrejevic 2012, 85). Such “external, storable, and sortable collection of data about” users’ “social lives” is “separated from us and stored in servers owned and controlled by, for example, Facebook” (Andrejevic 2011, 88). “Algorithmic alienation” (Andrejevic 2014, 189) determines users’ lives by data mining, big data analysis, and statistical correlations.

Eran Fisher (2012) understands digital alienation in a different way. For him, it “signals an existential state of not being in control over something (the labour process, the product, etc.)” (Fisher 2012, 173). Less “alienation refers to a greater possibility to express oneself, to control one’s production process, to objectify one’s essence and connect and communicate with others. Thus, for example, working on one’s Facebook page can be thought of as less alienating than working watching a television program” (Fisher 2012, 173). Social media

establish new relations of production that are based on a dialectical link between exploitation and alienation: in order to be de-alienated, users must communicate and socialize: they must establish social networks, share information, talk to their friends and read their posts, follow and be followed.

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Current Key Areas of Research

By thus doing they also exacerbate their exploitation. (Fisher 2012, 179)

Fisher’s conclusion is that on social media, low alienation creates high exploitation.

Andrejevic and Fisher have two different understandings of digital alienation. For Andrejevic, it is an objective condition, while for Fisher it is a subjective feeling. We do, however, not have to categorically separate subjective and objective alienation. Alienation is both an objective condition and something that is or is not felt. In the book Critical Theory of Communication (Fuchs 2016), I have suggested a matrix of alienation that distinguishes three types and three dimensions of alienation. We can discern between economic, political, and cultural alienations. Each of these types is organised on the subjective level (attitudes and feelings), the intersubjective level (social agency and interaction), and the objective level (structures and products of activity). Combining these types and levels results in a matrix with nine forms of alienation (Fuchs 2016, 167). The alienation matrix can be applied to Facebook and other commercial social media platform (see Table 8.1).

One important aspect of the matrix of digital alienation is that it goes beyond the economic realm. It also covers forms of political control and cultural disrespect. Social media is also a realm of the accumulation of political and cultural power that produces winners and losers. Another important aspect of the matrix is that objective digital alienation does not automatically imply subjective digital alienation. Although Facebook users are objectively exploited, they do not necessarily feel exploited, seeing that there is inverse commodity fetishism on corporate social media platforms. We therefore have to distinguish between feelings of digital alienation and non-alienation. In general, there is only an opportunity for societal change when conditions and the collective structure of feelings of alienation coincide. There is, however, also no guarantee that such change will automatically or necessarily be politically progressive in character.

8.4 Directions for Future Research

Studying social media and big data from a critical marketing perspective is interesting but also complex. It involves multiple dimensions, topics, questions, and approaches. This section identifies possible research questions that remain fairly unexplored and could be taken up by PhD students and other scholars. The list that follows is not complete, rather, it provides some examples.

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Source: Fuchs (2016, 171).

• What are commonalities and differences between users’ attitudes towards targeted advertising in Western countries and non-Western countries in Asia, Africa, and Latin America?

• How do traditional trade unions use social media and what do they think of the possibility of the creation of digital labour unions?

• What have workers’ and users’ experiences been in the digital sharing economy (including Airbnb, Uber, and online freelancing platforms such as Amazon Mechanical Turk and Upwork)?

• What are the experiences and political attitudes of digital workers in the international division of digital labour? What do they think of the perspective of the world’s digital workers uniting in a global movement or union?

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• What have been the experiences of people who have tried to establish alternatives to Facebook, Google, YouTube, Twitter, etc.? What problems have they faced? What challenges, limits, and problems do platform co-operatives face? Are there ways for such limits to be overcome?

• What kind of class are professional YouTubers? What kind of class consciousness do they have? How do they think about capitalism, entrepreneurship, neo-liberalism, freelancing, and precarious labour?

• How has marketing and advertising based on big data and social media changed the film and music industries? What do artists think about these changes? What is the role of precarious labour among artists in the social media age?

• How do right-wing parties and social movements (Trumpism, pro-Brexit movement, Front National, nationalists, racists, xenophobes, etc.) use targeted advertising, big data, and social media to advance their ideologies? How do they use social media as forms for political communication? What do everyday users think about such advertisements and right-wing online communication?

• How does marketing and targeted advertising change with the rise of the Internet of Things? What dangers do such forms of advertising entail? What do actual or potential users think about these dangers?

• What are the limits and problems of big data? How do users think about big data based advertising and targeted advertising? How do they think about noncommercial, commons-based, non-profit alternatives?

• How can an alternative paradigm to big data positivism and computational social science be established? What critiques can be levelled at these largely quantitative approaches? What alternative critically oriented social media research methods do we need to develop and how can they be applied to ideology critique?

• How are specific forms of ideologies expressed on social media?

• What policies are needed for advancing non-commercial, non-profit, commonsbased social media?

• How can the logic of social media and online communication be decelerated and the political public sphere thereby be best advanced? What are slow media 2.0? What are the potentials of slow media 2.0?

• What are the dangers of branded online content and native online advertising? How does branded online content and native online advertising make use of big data? What do users think of branded online content? What are the dangers for journalism stemming from these forms of content?

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• What problems does labour face in the context of crowdfunding? What power asymmetries and ideologies can we find in the world of crowdfunding? What have been experiences of actual project co-ordinators on crowdfunding platforms such as Kickstarter? How does crowdfunding relate to neoliberalism and the ideology of entrepreneurship?

• What controversies develop when digital advertising gurus meet digital labour activists in focus groups to debate digital capitalism?

8.5 Conclusion

Social media and big data are relatively new phenomena. At the same time, they reflect old power structures, but in new ways. This chapter focused on the analysis of social media’s political economy based on various critical theory approaches. It used classical concepts such as the audience commodity, audience labour, and commodity fetishism to show that critical analysis of advertising and targeted advertising needs to look at both economic and ideological dimensions. Facebook and Google are not communications corporations but the world’s largest advertising agencies. Current research in critical social media studies focuses on issues such as digital labour and digital alienation. Given that social media and big data will not disappear overnight, the critical study of these phenomena remains an important task.

References

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Chapter Nine Social Media and the Capitalist Crisis

9.1 Introduction
9.2 The Capitalist Crisis
9.3 Targeted Advertising and the Crisis
9.4 Social Media Ideology #1: “Twitter and Facebook Revolutions”
9.5 Social Media Ideology #2: Red Scare 2.0³
9.6 Conclusion
References

9.1 Introduction

In this work, I focus on discussing selected aspects of the relationship between social media and the capitalist crisis. Detailed critical analyses of political, economic, and ideological aspects of social media can be found in associated publications (Fuchs 2014a, 2014b, 2014c, 2015, 2016a, 2016b, 2016c, 2017; Fuchs and Mosco 2016; Fuchs and Sandoval 2014; Fisher and Fuchs 2015; Trottier and Fuchs 2014; Fuchs et al. 2012). I first summarise my analysis of the crisis (section 9.2), then discuss aspects of targeted advertising (section 9.3), the ideology of Twitter revolutions (section 9.4), and anti-socialist ideology on Twitter (section 9.5). The basic point the chapter makes is that capitalist development is an important factor that has conditioned the emergence of social media, social media’s economy, and ideology on social media.

9.2 The Capitalist Crisis

The profit rate is a key category of Marxist political economy (Marx 1867, chapter 17;
for a discussion see: Fuchs 2016b, chapter 17).

The rate of profit is the relationship of profit and investment or of the monetary expression of surplus-value and the value of the means of production (constant and variable capital).

$$
R O P = { \frac { s } { c + v } }
$$

DOI: 10.4324/9781003222149-9

If we divide the numerator and the denominator by v, then we get:

$$
R O P = { \frac { \frac { s } { v } } { { \frac { c } { v } } + 1 } }
$$

This formula shows that the rate of profit depends: (a) on the rate of surplus-value that Marx also calls the rate of exploitation because it described the relationship of unpaid and paid labours; and (b) the organic composition of capital that represents the relationship of dead and living labour, constant and variable capital, the value of machinery/resources, and labour-power. The organic composition is a measure of an economy’s technological intensity. The rate of profit is directly proportional to the rate of surplus-value and indirectly proportional to the organic composition of capital.

New technology has the potential to increase both the rate of surplus-value and the organic composition of capital. The effects of new technology on the rate of profit depend on the relationship between the rate of surplus-value and the organic composition. If the organic composition increases more than the rate of surplus-value, then a fall of the rate of profit emerges. Vice versa, if the rate of surplus-value increases more than the organic composition, then the rate of profit rises. An important factor in this respect is class struggle that influences the absolute value of variable capital v. In any case, the formula for the rate of profit shows that technification has contradictory potentials: it can increase productivity and the exploitation of labour.

The increase of the organic composition as structural tendency of capital stands in a contradiction with class struggles. The outcomes of this contradiction cannot be predicted in advance, but depend on historical circumstances. If the organic composition increases and there are no or unsuccessful workers’ struggles so that the wage sum decreases, then the rate of profit can increase. If however workers’ struggles are successful and they resist lay-offs and achieve wage-increases, the profit rate is more likely to fall.

Figures 9.1 and 9.2 show the development of the rate of profit, the organic composition, and the rate of surplus-value in the USA and the EU15 countries.

The rate of surplus-value, that is, the degree of exploitation, has decreased in the 1960s and was relatively low in the 1970s in both the USA and the EU15. This is an indication that the working class’ struggles were relatively successful in this time period and resulted in relative wage increases. In the early 1980s, the time of the rise of neoliberal politics such as Reagonomics and Thatcherism, the degree of exploitation started a long-term increase caused by wage repression.

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The time period 1960–2015 is one, in which the computer has arisen, shaped, and transformed capitalist economies. As a result, both in the USA and the EU15 countries the organic composition has, in this period covering 55 years, increased from around 20% to almost 30%, which confirms Marx’s analysis that there is a tendency of the organic composition to rise that results from the technification and scientification of production. The rate of profit in both the USA and the EU dropped as a result of increasing wages and the working class’ struggles in the 1960s until the middle of the 1970s, the time of a large global economic crisis. In the decades following the mid-1970s, the increasing organic composition puts a downward pressure, and the increasing rate of surplus-value put an upward pressure on the rate of profit. The microelectronic revolution extended and intensified the role of technology in capitalism and financing computerisation accounted for a growing share of total capital. As a result, the rate of profit both in the EU and the USA fluctuated and never returned to the rates it had reached in the 1960s.

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The Capitalist Crisis