Data analysis

CA’s analytic processes were explicated in various methodological literature (a small sample of such textbooks including Ten Have, 2007; Heath, et al., 2010; Hutchby & Woffitt, 2006; Liddicoat, 2011; Seedhouse 2004.) I adhered to the general analytic structures suggested by CA practitioners above. Specifically, the first phase of the data analysis was proceeded with a preliminary review of the corpus. In other words, I viewed every single recording whilst taking notes of episodes based on sequences, as a catalogue form. This form is made of a simple excel spread sheet including several columns as follows: nationality; the year when the interviewee first came to South Korea; the language of the interview, the length of the interview; topics and key interactional phenomena (detail/time code); and additional column for some verbatim quotes that I might look into later for further analysis. As such, I went through the entire dataset whilst making a comprehensive catalogue of the interview interactions.

After completing the preliminary stage, I moved on to the second phase of

analysis involving a substantive review and transcription. That is, I selected some moments of interviews, which draws my attention. Then, I transcribed them by employing the CA convention (see appendix A). I used Transana software package, which enables me to import video or audio clips and produce multiple transcripts. The software allows me to time code each fragment and precisely match utterances of participants with the corresponding frames of video clip. Whilst doing this, I was still in a mode of ‘unmotivated looking’ (Psathas, 1995) That means I did not have a particular substantive topic or analytic focus in my mind whilst watching and transcribing some segments of the corpus.

Nevertheless, after generating about ten excerpts through Transana whilst

applying the CA transcription convention, several interactional features relating to a story-telling began to emerge as candidate analytic phenomena: represented talk; embodied assessment; the interviewer’s self-disclosure as an attempt to align or

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affiliate with the prior turn uttered by the interviewee; the use of category- resonant terms.

Presenting excerpts in different data sessions (e.g. MARG) was one of the central parts to move from the preliminary review to a substantive review of the corpus. Data sessions are a type of collaborative observation, which play a critical role in general principles and practices of CA studies in various disciplines (Ten Have, 2007) (see section 3.4.1). Put more simply, ‘an informal get-together of

researchers’ in order to discuss a fragment of a dataset composed of a video or audio clip/excerpt transcripts (ibid: 140). In general, a data session tend to go through several stages as follows: A researcher bring her/his data recording normally less than three minutes and its CA transcript consisted of approximately two or three pages. Then, the researcher plays the video or audio recording after distributing the transcript to the members of the data session. Whilst playing the recording several times, the members are watching, listening and reading the clip and its transcript. If necessary, the presenter explains additional background information after playing the video or audio clip, which might be helpful to grasp the interaction and its relevant context. After this phase, each member brings their own observations by raising questions, providing different points of views and suggesting relevant studies as an exchange of a range of discussion points in relation to the presented segment. I also went through these processes when I presented my data in several data sessions inside and outside of the university, and these allowed me to gain analytic insights and useful comments from other

researchers working on different types of EMCA studies. It also enabled me to enhance reliability and validity of this study. That is, I was able to scrutinise my data from a different angle and discover seveal candidate analytic points, thereby moving forward to the next stage of the analysis.

The final stage of the analysis is dedicated to build up collections in order to identify particular conversational phenomena. Building up a collection has been highlighted by CA analysts as a way to generate ‘analyses of patterns in the sequential organisation of talk-in-interaction’ (Hutchby & Wooffitt, 2006: 93). Indeed, this process aims to identify similar patterns in a corpus to achieve a deeper understanding of the phenomena (Liddicoat, 2011). The collection of the

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candidate activities also enables the researcher to discover orderliness and

regularities of the interactional phenomenon across the dataset in order to make a robust analytic claim. The most important thing is that the main aim of building up a collection is not drawing statistical defences (Heath, et al., 2010). Rather, it is more about excavating sequential contexts by examining the types of turn, which are placed before/after the phenomenon.

Considering the suggested instructions from the CA literature, I started collecting a number of instances revealing particular interactional business: the interviewer’s self-disclosure in various types of sequences (e.g. a story-telling regarding

difficulties an interviewee had encountered in the past) and total 64 instances were collected. Then the cases are reorganised and reanalysed to provide more

systematic descriptions of sequential organisation and categorical work embedded in the interviewer’s self-disclosure and the following three broad questions were applied to the process: 1) what kind of things lead to self-disclosure by

interviewer?; 2) what kind of things are self-disclosed and how are self- disclosures formulated?; 3) how are self-disclosure responded to? Numerous interesting phenomena were discovered; however, the second question was particularly developed as the overarching research question of this thesis as introduced in chapter 1. The relevant answers will be provided in detail throughout the forthcoming analysis chapters.

4.7 Summary

In this chapter, the overview of the research context has been illustrated by focusing on research setting (section 4.2), recruited participants (section 4.3), researcher positionality/reflexivity (section 4.4), ethical consideration (section 4.5) and data analysis (section 4.7). The elaborated contexts so far provide a broader picture of the current research by briefly introducing when and where the data generation occurred, along with the two important elements of this research: who the main participants are, and how the generated data was analysed at the beginning stage of this project. In doing this, not only the general information of

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the interviewees were described, but also the positionality of the interviewer was explored whilst emphasising how the researcher reflexivity is operated under the CA principles. Such attention to the researcher’s multifaceted identity is built upon the discussion on the contructionist conception of interviewing (Chapter 2), the theoretical underpinnings of CA and MCA and the ensurance of

realiabilty/validity (Chapter 3). Of course, this will be the fundamental basis of the forthcoming analysis chapters and discussion chapter.

Having examined the research context and process, it is appropriate to move on to report the empirical findings of this study. This will be done in the following analysis chapters with relevant CA excerpts.

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