Towards Democratisation?: Understanding university students’ Internet use in mainland China
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- 3.6.2 Emerged categories
- 3.6.3 The participants
- 3.6.4 Other media use
3.6 Data analysis3.6.1 Four coding phrasesCoding was conducted using NVivo 10. There are worries about loss of closeness to the data due to ‘poor screen display, segmentation of text and loss of context’ (Bazeley, 2007, p.8) or loss of distance from the data when using software for data analysis (Richards, 1998; Gilbert, 2002). Qualitative research needed both ‘closeness and distance: closeness for familiarity and appreciation of subtle differences’ to see from the insider’s perspective, but distance ‘for abstraction and synthesis’ to provide an outsider’s view – and ‘the ability to switch between the two’ (Bazeley, 2007, p.8). NVivo 10 ensures closeness, distance and an ease to switch between the two when needed for sophisticated analysis that characterises qualitative research (Bazeley, 2007). Figure 2: Demonstration of open coding using NVivo 10 
List View Detail View Navigation View Timespan Recording Figure 2 demonstrates how NVivo 10 is utilised at the open coding phase. Transcript is displayed in Detail view and Timespan shows the time span of the corresponding transcript in the recording, which allows the researcher to retrieve the original data easily when there is doubt about the transcript or when the researcher wants to recall some information that the plain text transcript cannot express. The researcher can code the text or the recording, if transcript is not needed, by simply selecting the text or the recording, right clicking the mouse, and then choosing ‘Code Selection At New Node’. An interface appears as Figure 3 shows. The researcher can then name and describe the code, click ‘OK’, and then the chosen text will be stored in a node under the name as a ‘Reference’. The established codes can be seen from List View (see Figure 2). New texts of the established codes can be coded into them as new references. A reference can be displayed in the Detail view by double clicking its name in the List view. The researcher can easily retrieve the context of the reference by double clicking it or by highlighting the code in the transcript. Figure 3: Demonstration of coding using NVivo 10 
Open coding Methodologists (Charmaz, 2006a; Strauss, 1987; Bazeley, 2007) suggested to use in vivo codes that are derived directly from the data at the open coding phase, which means naming a code with an actual expression of a participant instead of a sociologically or theoretically constructed code. For example, P01 said, “I am just showing my concern (online). You cannot influence the decision-making of the above (the government)” (see Figure 3). The two sentences were coded with the name of ‘Unable to influence decision-making’ as P01 expressed it. Significant codes like ‘Want to go bicycling when reading bicycling blogs’ and frequent codes like ‘Online shopping’ were generated. The first three volunteering participants were all male students. The researcher wanted to see if gender makes a difference on the research topic. Therefore, at the next stage, a female university student from Chongqing University was recruited. According to the findings of open coding, the interview has been refocused. Greater attention has been paid to the online activities that were conventionally considered not-that-political such as online shopping, sharing of the participant’s lifestyle content and so on. Focused coding Focused coding is the second major phase in data analysis, but it is the first step to move from specific data and participants’ expressions to more general, abstract, directed, selective, and conceptual categories or themes that have the capacity to encompass and explain larger segments of the data than single lines (Charmaz, 2006a; 2006b). This phase, as its name indicates, focuses on the most significant and frequent earlier codes (Charmaz, 2006a). For example, in the selected text in Figure 4, P02 explained how he categorised his QQ friends. In the previous phase, the selected text was coded line by line into nodes named ‘Senior high schoolmates’, ‘University classmates’, ‘Family’, ‘CQUPT (Chongqing University of Posts and Telecommunications) girls’, ‘CQUPT boys’, and ‘New friends’ using P04’s own words. In the focused coding phase, the whole text was coded under an umbrella node labelled ‘QQ contact categories’. Figure 4: Demonstration of focused coding using NVivo 10 
Axial coding As a result of focused coding, categories emerged from the data. The purpose of theoretical sampling and data analysis at the next stage is to collect data to specify the properties and dimensions of the emerged categories. This phase of data analysis is named by Strauss (1987) ‘axial coding’ by which he meant conducting ‘intense analysis around one category at a time in terms of paradigm items’ in order to build ‘a dense texture of relationships around the axis of a category’ (p.32). Similarly, both focused coding and axial coding are approaches used to sort and synthesise large amounts of data. Different from focused coding which is still text-based, axial coding aims at organising large amounts of data and reassembling them in new ways around categories. It is through relating categories to subcategories (Charmaz, 2006a) that one can achieve a clear definition of emerged categories. The ultimate product of axial coding is saturated categories. Therefore, Draucker, et al. (2007) suggested that ‘axial coding requires relational, or variational, sampling, in which data are gathered to uncover and validate the relationships among categories that have been discovered’ (p.1138). Results from focused coding indicated that four participants were more similar than different in their online activities and their understanding of their online activities despite the fact that differences do exist. The enclosed Chinese Internet is blamed as the major shackle on the liberating power of the Internet in mainland China (Lagervist, 2006; BOAS, 2004; Edelman, 2003; Fry, 2006; Gorman, 2005; Harwit and Clark, 2001; Jiang and Xu, 2009; Palfrey, 2008; Qiu, Winter 1999/2000; Weber and Jia, 2007; Zhang, 2002). To add variation to Internet use, the researcher decided to explore if using tools to climb over the Great Wall would make a difference. Two participants from Sichuan International Studies University, thus, were recruited through an associated professor at the University. They were P05, a female English undergraduate in her final (fourth) year who did not use any tool to access the filtered content online, and P06, a male English undergraduate in his first year who climbed over the Great Wall to access the filtered content online. The two interviews were also refocused to serve the purpose of data collection. All online activities of the two participants were intensively investigated, but special efforts were made to explore the online activities made possible because of their English skills and because of P06’s climbing over the Great Wall. New data collected by interviewing P05 and P06 went through the process of open coding and focused coding to uncover new categories. And then category-centred axial coding was conducted to define emerged categories from the previous coding and to relate categories to subcategories. Saturated categories were yielded. The purpose of the next step was to generate saturated core categories. A focus group was conducted to serve the purpose. Theoretical coding Theoretical coding is a sophisticated level of coding that follows the codes selected during axial coding. The purpose of theoretical coding is to verify or to build theories. As one of the founders of grounded theory, Glaser (1978; 1992) has elaborated on what constitutes theoretical codes and how to find relationships between codes. According to him, theoretical codes conceptualise ‘how the substantive codes may relate to each other as hypotheses to integrated into a theory’. Theoretical coding is the process of generating theoretical codes that specify relationships between categories that emerged from axial coding. Glaser (1992) argues that theoretical codes and axial codes were different. Axial codes distinguish categories from categories, while theoretical codes ‘weave the fractured story back together’ (Glaser, 1978). Theoretical codes served to tell coherent analytic stories (Charmaz, 2006a). The final phase of data analysis consisted of three steps. In the first step, new data produced by the focus group went through the first three phases of coding to see if new categories would emerge. To ensure that the emerged categories were clearly defined and also to bring fresh insights into the research, the second step involved a team of four coders to discuss the definitions of the emerged categories, to code one or two transcripts of interviews independently, and to discuss again the clarity of the definitions and their insights about the research topic based on the data. The four coders were three third year PhD students in the Department of Journalism Studies and one first year PhD student in the Department of English at the University of Sheffield. The four coders were all Chinese and they coded from the Mandarin. Based on the discussion with the coders, memos, and checking the result of coder’s independent coding, the researcher refined some of the categories. In total, 3,408 references were yielded, and gathered under the emerged codes. With such rich data falling under a relatively small number of categories, the properties of forty-one categories are clearly defined. Then the researcher moved on to the next stage, theoretical coding, to relate the categories and subcategories to each other aiming to uncover participants’ patterns of Internet use, their understandings of their use patterns and their effects. Theoretical coding found the patterns of how an individual employs different Internet applications for different purposes to serve his or her needs and new interpretations of patterns of Internet use deemed non-democratising by the participants from their perspective (displayed and discussed in Chapters 4-6). Those findings are theoretically significant and innovative, and are based on and sufficiently supported by the data. Therefore, the saturation point of data collecting has been reached.
Table 4. Categories emerged from the focused coding
3.6.3 The participantsThe concept of ‘participant’ encompasses three components: five demographic features, online skills, and how a participant described himself/herself in the interview or the focus group. Table 5. Who are the participants?
Notes: Yos = Year of study; Catshs = Course at senior high school; CQUPT = Chongqing University of Posts and Telecommunications; CQU= Chongqing University; SISU= Sichuan International Studies University Table 6. Online skills
Table 7. Participants’ online skills?
Table 7 illustrates the online skills of the participants which were measured by the online skills scale (alpha = .75) created by Brian S. Krueger (2005). The scale consists of four items listed in Table 6. All twelve participants’ online skills were above average level and were at the same level. Table 8. How did the participants describe themselves?
Some participants expressed opinions about themselves in their interviews or the focus group to explain their online behaviours. Table 8 demonstrates how the participants described themselves. For example, the interviewer asked P01, “has there been any occasion when you wanted to say something, but chose not to because of the fear of censorship?” He answered, “no. I did not find that there was times when I really wanted to say something. It has become a habit of mine to just read.” Then he explained that the factor that affected his online expression was not censorship but how people saw him. He reported that he did not want to be seen as ‘fringe’. Arguably, a political culture preferring unification of thought to diverse ideas (see Chapter 2) affected P01’s online behaviour. He felt that he was known as a moderate person who never went to extremes among those who knew him. He claimed, therefore, he would think over and he would not make extreme comments on the online platform on which the people who read his comments knew who he was. He gave an example of what he meant by extreme comments. He said, “for example, having read about a conflict between China and Japan, some people will comment, ‘start a war with Japan’. It is extreme and impossible.” Yet on a platform where his readers were strangers, he reported that occasionally he probably made some extreme comments. It indicates that anonymity of online environment freed P01 from the political culture to some degree. When he explained why he made comments about news online, he attributed it to his character. Both P01 and P02 attributed their online behaviour more or exclusively to personality than to censorship. P06 reported that he could make comparisons between Eastern and Western cultures, or between different ideologies, their ideologies or views of the world, or values to see which aspect most suited him by reading both domestic and foreign news reports. He claimed that he was inclined to believe in the Western values when asked. According to P06, the Internet became a source of alternative ideology. P09 reported that he loved history including both the ancient and modern history of China when he explained how the Internet helped him see things from different perspectives and precipitated him to think. He clearly showed a sense of superiority over most Chinese people. P11 claimed that she was not interested in the topic of climbing over the Great Wall after listening to P07 and P09’s experience and understanding of their climbing over the Great Wall. She also reported that she thought that women were much less involved in political participation or discussion. To sum up, how the participants described themselves show that they tended to consider their online behaviour as personalised to meet their own needs, and think that their personality determined their online behaviour and how they were influenced by their online behaviour. 3.6.4 Other media useTable 9. Other media use
Not surprisingly, participants are found to use the Internet as their major medium, if not the sole medium. The studied population are required to stay in university-provided dormitories which do not provide TV or any other mass media other than Internet access. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||