Читать книгу An Introduction to Text Mining - Gabe Ignatow - Страница 24

In the 1990s, researchers began to adapt ethnographic methods designed to study geographically situated communities to online environments which are characterized by relationships that are technologically mediated rather than immediate (Salmons, 2014). The result is virtual ethnography (Hine, 2000) or netnography (Kozinets, 2009), which is the ethnographic study of people interacting in a wide range of online environments. Kozinets, a netnography pioneer, argues that successful netnography requires researchers to acknowledge the unique characteristics of these environments and to effect a “radical shift” from offline ethnography, which observes people, to a mode of analysis that involves recontextualizing conversational acts (Kozinets, 2002, p. 64). Because netnography provides more limited access to fixed demographic markers than does ethnography, the identities of discussants are much more difficult to discern. Yet netnographers must learn as much as possible about the forums, groups, and individuals they seek to understand. Unlike in traditional ethnographies, in the identification of relevant communities, online search engines have proven invaluable to the task of learning about research populations (Kozinets, 2002, p. 63).

Just as the quality of social survey research depends on sampling, netnography requires careful case selection (see Chapter 5). Netnographers must begin with specific research questions and then identify online forums appropriate to these questions (Kozinets, 2009, p. 89).

Netnography’s lessons for text mining and analysis are straightforward. Leading researchers have shown that for netnography to be successful, researchers must acknowledge the unique characteristics of online environments, recognize the importance of developing and explaining their data selection strategy, and learn as much as they possibly can about their populations of interest. All three lessons apply to text mining research that analyzes user-generated data mined from online sources.