4.3 Research Procedure and Method
4.3.2 Method of Data Analysis
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informed consent, which are contained in the survey. The survey was reposted several times afterwards to encourage members to participate.
Given the nature of my study, I think it is important to note here that although the survey was administered online with no direct interaction with the participants, it was nonetheless an interactive process. In my introduction, I thanked the leadership of the Forum for allowing me to conduct the survey. This was a deliberate process that aimed at providing me with some level of credibility among the forum participants, especially among those members who did not know me in person. The post received many ‘likes’ and responses, mostly good-luck wishes. However, the site administrators were also called upon by a user to confirm my claims of being a Nigerian, of having obtained permission from group leadership, and to assure the group that I was reliable and not an intruder or someone with a hidden agenda. A few key members and administrators attested to my credibility, and explained that they had met me in person and that they were familiar with my research. Afterwards, most of the members who took the survey commented on the same conversation thread to say they had taken the survey, and to encourage others to do the same. A few also tagged or shared the survey to their friends, and one participant suggested that the findings of the survey be shared with the group.
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Braun and Clarke (2006) argue that in thematic analysis themes are identified using either an inductive (‘bottom-up’) or a theoretical (deductive, ‘top-down’) analysis. In the former, the themes are strongly linked to data, are not informed or determined by the theoretical interest(s), nor the analytic preconceptions of the researcher. In the latter, however, the analysis of data is driven by the analytic and theoretical interest and preconceptions of the researcher in the area of study. This method of analysis focuses more on providing detailed analysis rather than richly describing the overall data. Ideas from one’s theoretical framework or concepts from previous studies may be employed to identify themes and analyze them.
My method of analysis fell more, but not entirely, within the second category. It was driven by a postcolonial lens, which framed my study and research questions and objectives, as well as ideas from research in media and digital religion, which I draw upon to understand the invocation of, and practices related to, religion online. Postcolonial theory is concerned with deconstructing colonial history and its effects on present-day social relations and identities of both colonized and colonizer. Postcolonial theory takes seriously contexts of alienation and domination, and seeks to excavate acts of agency and resistance within them by privileging alternative (subaltern) voices and knowledges (Young, 2003; Rattansi, 1997). Thus, postcolonial theory provides a specific way, a point of view, and an interest in reading data. Using this lens, I read my data to identify, code, interpret and analyze representations of identity as they emerged in online rhetoric, practices and narratives about religion and ethnicity in Kaduna on the Online Forum.
The concept of digital religion which I used to understand online articulations and practices of religion as well as the mutual shaping of religion and digital media and spaces (Campbell, 2013), also informed my reading and coding of data. This made visible ‘religion’ and ‘the religious’ and how these interact with the online platform and its features to manufacture/reproduce the representations identified using a postcolonial analytical lens.
‘Level’ of themes: semantic or latent
Another important decision, according to Braun and Clarke (2006), is about the ‘level’ of identification of themes. At the semantic (explicit) level, the researcher identifies themes at the surface, where the meanings of data are considered explicit. In this process, the analysis does not go deeper than what is explicitly expressed by participants or the text being analyzed. At the latent level, however, the researcher goes beyond the surface meanings of data (Braun and
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Clarke, 2006). Here, the assumptions, underlying ideas, ideologies, and stories that inform and shape the semantics are excavated and analyzed. I considered the latent approach appropriate for my study given the location of my research within the critical paradigm and postcolonial theory, as well as the ‘heavy’ history and stories that literature show to underlie the issues that my study population engage online. The examination of my data at a latent level helped me get deeper and more rigorously into my data.
Phases of Thematic Analysis
Recognizing that there is no fixed, wrong or right way to carry out a thematic analysis, Braun and Clarke (2006) suggest stages that a researcher may use to conduct a thematic analysis. These are the phases I adopted for my analysis of data because of their simplicity, clarity and flexibility.
Phase 1: Familiarization with data: In this phase I immersed myself in the collected data to get thoroughly familiar with the content. I did this through repeated and active reading of the data to be aware of patterns, search for meanings, and note ideas that were potentially relevant for coding and developing themes.
Phase 2: Generation of initial codes: In this phase I approached the data with specific questions in my mind. The questions were guided by my theoretical framework and my research questions, such as how are Hausa, Muslim, Christian or Southern Kaduna persons/groups defined? What words, phrases, ideas, suggest a certain picture, characteristic of the members of any of these ethnicities and/or religions, and/or serve as identity markers? While I did not read the data for specific answers to these and similar questions, having them at the back of my mind allowed relevant words, phrases, ideas to surface and to be coded. These were coded using colour- highlighting and notes on the PDF documents containing the raw data, as well as a marking system, includingsingle/double lines, zigzags, and other symbols, I developed to help me code print-outs of data.
Phase 3: Searching for themes: Here, the different codes generated were sorted into tentative themes and all appropriate data extracts for each theme were collated. During this phase, I began to analyze the codes and their relationships to each other in order to abstract and identify
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overarching themes. This phase of analysis produced a list of candidate themes and sub-themes, as well as their related data extracts and context of their production.
Phase 4: Review of themes: The candidate themes and coded data were reviewed thoroughly, to ensure coherence, validity and accuracy. I carefully read the candidate themes and related coded data. I also revisited previous phases of analysis to ensure that they were adequately followed and that I did not leave out any important steps.
Phase 5: Definition and naming of themes: At this phase, the themes were further named and grouped under three broad themes, namely; Representation of the Self, Representation of the Other, and Representation of Religion. The sub-themes were grouped into specific narratives under which they could be better examined. This also involved establishing the aspect of the data that was represented by each theme, and “identifying the ‘story’ that each theme tells” as well as
“how it fits into the broader overall ‘story’” of the data in relation to the research question (Braun and Clarke, 2006: 96).
Phase 6: Producing the report: I have attempted, in this phase, to produce a current research report in a logical and convincing manner.
Online Survey data: 108 responses were received from the online survey. The information collected was automatically tabulated in a spreadsheet using Google Docs, which made it easy to analyze using the Microsoft Excel 2013 Pivot table tool. The frequency and percentage relative to the total responses were calculated and presented in a tabular form for each question. During the analysis of data, both survey and collected online content were brought into conversation, which enhanced the meaning-making process by complementing and challenging each other.