A HyperLink Network Analysis of the UK Mobile Porn Industry

Abstract

The Internet is optimistically regarded as a force for democracy and at the same time another mechanism by which the poor and weak become further disempowered (Calhoun, 1998). Computer mediated communication enhances the current power structures while reinforcing the exploitation of those who are most vulnerable. By recognising the dominance of online pornography, Internet Service Providers and the communications industry are willing to accept the profits generated in working with the porn industry while ignoring the price being paid by the most visible, and yet voiceless agents. In doing so the Internet is awash with easily accessible pornographic imagery with mobile phones viewed as an even bigger market. With the demand for such material being the driving force for broadband usage and with the expansion of the use of mobile phones for downloading videos, I will ask; ‘which United Kingdom companies are the keyplayers? Are there structural holes within the networks, ensuring ‘deniability’ for the larger industrial players?’ I target online websites of the ‘adult entertainment’ industry in the UK using HyperLink analysis in order to extract the social network. This then enables me to conduct social network analysis uncovering the keyplayers of the UK porn industry with higher levels of “closeness centrality” and “betweenness centrality” (de Nooy et al., 2005). Closeness centrality and betweenness centrality are regarded as measures of power within a given network. This paper is an exploratory analysis of the dominant players shaping the UK mobile porn industry, searching for tentative links between the providers and the industrial players that have enabled the distribution of the material via the Internet and mobile phones. 

 

Results of crawl of 171 seed URLs resulted in a network of 970 nodes.

Results of crawl of 171 seed URLs resulted in a network of 970 nodes.

 

 

 

 

UK Mobile Porn Industry, 135 nodes with paths

UK Mobile Porn Industry, 135 nodes with paths

 

 

 

Steven McDermott

Institute of Communications Studies

University of Leeds

cssem@leeds.ac.uk

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