First, we begin with a discussion on factors potentially affecting users’ ability to select media content, as this has a bearing on users’ power over the production and distribution of media content. A user’s ability to actively select media content may be
influenced by factors such as the so-called ‘digital divide’, search engines’ customiza-tion capabilities and censorship practices.
5.1.1. The Digital Divide Affects User Power
It is argued that an information society does not necessarily equal an informed so-ciety (Selwyn, 2004:257; Introna and Nissenbaum, 2000). The term ‘digital divide’
initially was coined to describe the inequality of people’s access to knowledge-gaining devices such as telephones, computers and the connecting network infrastructure, and, later, the quality and speed of those connections. Put simply, the digital divide describes the divergence between those who have access to knowledge versus those who have not. The UN Millenium Development Goals in 2000 set targets to decrease the number of those who do not have physical access (United Nations, 2013).
Van Dijk and Hacker (2003) suggest we look at access from the perspective of an iterative four-step process beginning with motivational access as the first step. This first phase of motivational access involves the user’s social, cultural or psychological background. Pro-ams (professional amateurs who tend to be more motivated to par-ticipate than, for example, passive users) move quickly from this initial phase to the next. The second phase is the user’s material access, such as income and education, which affects the user’s ability to have a computer and Internet connection. The third skills access phase involves operational, informative and strategic knowledge of the use application. For example, a person might have an application such as Adobe Pho-toshop available but s/he may not know how to use it to produce and publish quality pictures online. A person might have a Twitter account but does not how to use it actively and effectively. The final usage access phase is the stage in which a person actually uses the application, even though s/he may still remain passive (Van Dijk and Hacker, 2003). Van Dijk and Hacker argue that it is this final usage access phase that seems to be building a larger gap between users today. On the other hand, we agree with Haramban et al. (2013) who emphasize the first phase as the problematic phase in this process, namely that motivation (see earlier section in this chapter) is vital in understanding the digital divide today.
Fig. 3. Dimensions of Access in Defining the Digital Divide (Van Dijk and Hacker, 2003:315-316, adapted as in Ghobadi and Ghobadi, 2013)
According to Selwyn (2004), the digital divide inevitably has transitioned from a comparison between countries to divisions within countries. In addressing this gap, he proposes that the focus should be on the content that access gives users, rather than on the technologies being used. Selwyn suggests that a better understanding of the impacts or consequences of using ICT (information communication technology) can be avoided by the term ‘meaningful engagement with ICT’ through examining users’ participation in activities such as production, political, social, consumption and savings activities in society (Selwyn, 2004:350–351). In essence, Selwyn calls for ex-tending our understanding of the digital divide as part of a larger discourse on social inclusion in societies. Some researchers argue that societal structures, including asym-metrical power relationships, may have been replicated to the Internet, preventing societal development progressing (Castells, 2009; Introna and Nissenbaum, 2000).
Debates centred around increasing social inequalities raise concerns about whether equitable access to media leads to an equitable information society. It is believed that societal structures either impede or encourage the use of media. Through the roll-out and provision of new technologies, for example, some societies may leapfrog older technologies providing citizens with increased access to media content. As an example, some nations experience high mobile phone penetration compensating for low numbers of fixed phone lines. Interestingly, according to a 2012 Semiocast com-mercial study heavily populated countries such as Brazil and Indonesia are among the most popular Twitter locations, with Jakarta leading Tokyo and New York in terms of frequency of tweets sent by cities (Semiocast, 2012).
Whilst socio-economic aspects such as age, education and users’ income affect the digital divide, another key influence is motivation to seek information and to actively participate in content production and distribution (e.g., Straubhaar, LaRose and Davenport, 2013:438).
5.1.2. Censorship and Customization
Censorship is another obvious factor limiting users’ ability to select media content.
One way to exclude the views of those not sanctioned by governments or mainstream media, such as bloggers and vloggers, whether pro-am or not, is through censorship – the various selection-limiting practices imposed by government agencies and Internet service providers (ISPs). MacKinnon (2008) examined how the Chinese blogosphere has enabled social change in China to slowly evolve and the practices the Chinese government use to manage this digital discourse space. For instance, private service providers also practice a form of self-censorship in scanning, monitoring and censor-ing content. Users’ selection power therefore might remain limited, if only a small proportion have the skills and technology to bypass these barriers (MacKinnon 2008;
Ghobadi and Ghobadi 2013).
Another more subtle way of limiting possibility to select media content is through customization. While media producers have traditionally selected the content offered to the users, today search engines do such selection automatically. This is enhanced by the increasing maturity of the options for providing hits to users seeking informa-tion based on rankings such as popularity or recommendainforma-tions or simply on users’
online behaviour (see Bucher, 2012). When Introna and Nissenbaum (2000:181) called for transparent disclosure of the practices used to formulate search engines’
algorithms including rules for searching, indexing and prioritizing, these search en-gines were still in their infancy compared to their capabilities today (see Hyppönen, 2013). This may limit the users’ power to select desired content when content is not even visible to choose from.