Critical approaches and methods to cyberculture studies

Baym, 2006 raises the question of quality in prevalent qualitative research on the Web and draws attention to the peculiarities of qualitative research methods as they apply to the Web. Her observations are valid particularly about the standards that characterize good qualitative research. I would also include the experience of the researcher as an important determinant of the quality. In addition, data triangulation may also serve as an indicator of good quality. It would have been helpful if Baym, 2006 had provided statistics giving an insight to what percentage of the research conducted on the Internet was qualitative. It would also be interesting to know what types of qualitative research methods were used. Were they interviews, focus groups, historical reviews, case studies, generic analysis (a method of rhetorical criticism), or experiments? Web research, one would assume is more amenable to quantitative research, for instance online surveys or content analysis.
The Web sphere analysis method articulated by Foot, 2006 appears to be promising although in most cases the Web site developer may not be the content developer too. In most corporate, government (federal, state, or local), institutional or commercial Web sites the Web site is designed by the IT department whereas the content is determined by another individual or set of individual. If the researcher is investigating the Web for socio-political content the Web sphere analysis might prove useful however, if one has to explore the structural dynamics Web sphere analysis would not be an appropriate choice.
Both Sandvig, 2006 and Elmer, 2006 individually seem to agree that the Internet may not be the boon for cyber culture development and proliferation. It is interesting to note how Elmer, 2006 views the hierarchical operationalization of content as being a barrier to the development of cyber culture and by implication the empowerment of individuals. “Web has become increasingly operationalized through hierarchical methods and subtly directs users towards preferred—and allied providers of — content goods and services.” (p.159). Sandvig, 2006 also draws attention to the fact that the inherent design of the Internet may be to blame or responsible for stifling the production of cyberculture. That may be so. I would however, argue that the sites that have become popular or boast of large number of site visitors also started as nameless or insignificant Web sites or blogs etc. This suggests that Elmer's, 2006 and Sandvig’s summarization may be fallacious and it would be probably more apt to state that Internet or the Web discriminates between content as any other media does between what is good, what is not so good, and therefore, what is popular and not so popular.
Another aspect that was puzzling was the framing of the digital divide in terms of “digital destitution.” Gordo, 2006 defines “digital destitution” as the negative consequences of digital divide that arises because of the technology-based alienation and deprivation to participate, compete, and prosper in today’s knowledge-based economics. At the outset, it appears as old wine in a new bottle. Her basic concern is how community-based organizations can use technology to support low-income populations if there are no policies mandating organizations to integrate information technology into work processes and social service delivery systems. She uses extensive schematic representation to represent the development of community technology and elements that measures the pace of development but how does Community Training Center (CTC) like Plugged In help at the practical level to reverse the digital destitution. What policies are currently in place? Her resolution of the digital destitution issue raises more questions than answers. Nevertheless, as long as the policy researchers ask questions and they attract attention and debate, it is a good sign.