This thesis examines the problem of racist disinformation on the World Wide Web and the role played by anti-racist sites in providing balance. The disinformation capacity of the Web is an important issue for those who provide access to the Web, for content providers, and for Web users. An understanding of the issues involved, including the characteristics of racist disinformation, is vital if these groups are to make informed decisions about how to deal with such Web content. However, in Australia especially, there has been limited research into racism in general and racism on the Web in particular. To address this deficiency, the integration of perspectives from the fields of race relations and information science is facilitated utilising a critical realist methodology to provide new insights. Through an extensive examination of the literature, including Australian media reports, terms are delineated and the problem situated within an historical, cultural and political environment. Alternatives for tackling racist disinformation are evaluated and the issues involved in the provision and utilisation of balancing information are discussed. The literature analysis underpins an assessment of anti-racist sites using three data collection methods to gain multiple perspectives on the balancing qualities of these sites. These methods are an assessment of anti-racist website longevity, an assessment of website reliability, and a questionnaire of content providers of anti-racist websites. This thesis provides a synthesis of the academic literature and media coverage related to Australian racism and racist disinformation on the Web, leading to new insights about the range and depth of issues concerned. An analysis of the data collected concludes that while anti-racist websites take on diverse roles in tackling racism, few provide content directly to balance Web racist disinformation. Approaches that seek to control or censure the Web are ineffective and problematic, but balancing disinformation is not in itself an adequate solution.
Identifer | oai:union.ndltd.org:ADTP/210246 |
Date | January 2007 |
Creators | Skinner, Sally Ann, saskinner@bigpond.com |
Publisher | RMIT University. Business Information Technology |
Source Sets | Australiasian Digital Theses Program |
Language | English |
Detected Language | English |
Rights | http://www.rmit.edu.au/help/disclaimer, Copyright Sally Ann Skinner |
Page generated in 0.0018 seconds