Thematic Content Analysis in Literary Studies
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Although semantics has become world-famous in literary research throughout the twentieth century, it is not just word counts or objective objectives that are used to examine the content of a work; The reason is that researchers have suggested that characteristic content analysis may help in deeper understanding and excavating the underlying meaning of the texts. This article explores the need for characteristic content analysis and the steps to be taken to unravel the themes embodied in the work. In the study of literature, characteristic content studies can help to identify themes, to describe the data in the work, to compare with other data, and to intervene into the text.Keywords:
Content (measure theory)
Thematic Analysis
Thematic structure
Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it hopes to address the gap between qualitative methodologists' assumption of thematic analysis as a subjective, creative and flexible process and editors/reviewers' expectation that thematic analysis shall be objective, reliable and rigorous. By consciously and purposefully applying these cognitive processes, thematic analysis can be subjective and yet disciplined, creative and yet rigorous, flexible and yet reliable. The ultimate goal of this paper is to demystify, delineate and further demarcate the thematic analysis process for young and novice qualitative researchers.
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Abstract Thematic analysis is a poorly demarcated, rarely acknowledged, yet widely used qualitative analytic method within psychology. In this paper, we argue that it offers an accessible and theoretically flexible approach to analysing qualitative data. We outline what thematic analysis is, locating it in relation to other qualitative analytic methods that search for themes or patterns, and in relation to different epistemological and ontological positions. We then provide clear guidelines to those wanting to start thematic analysis, or conduct it in a more deliberate and rigorous way, and consider potential pitfalls in conducting thematic analysis. Finally, we outline the disadvantages and advantages of thematic analysis. We conclude by advocating thematic analysis as a useful and flexible method for qualitative research in and beyond psychology. Key words: epistemologyflexibilitypatternsqualitative psychologythematic analysis
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Research has a long tradition of quantitative research which still dominates many university courses on research methods. Qualitative research is a younger phenomenon that was established in research after the second world war. An emerging research field that needed new analysis methods tailored for qualitative data. Two of the most frequently used approaches in qualitative data analysis are content analysis and thematic analysis. In several aspects content analysis and thematic analysis both share a common approach to analytically examine qualitative data, and the fact that they have been used interchangeably has made it difficult for the more unexperienced researchers to distinguish and choose between them. The aim of this study is to examine doctoral students’ perceptions of qualitative analysis with content analysis and thematic analysis. The study had a qualitative approach with data collected from two webinars on qualitative data analysis, where a total of 76 doctoral students participated. Data consists of participant reflections in a Padlet on content analysis and thematic analysis at the two webinars. Webinar participants have given their consent to use their reflections in the Padlet for research. Content analysis with an abductive coding approach was used to analyse the collected data and formulate categories that answer the study’s aim and research question. Results show both perceived similarities and differences between content analysis and thematic analysis. Both are perceived to have a similar process in the coding of data, although content analysis has a wider selection of coding approaches and thematic analysis support deeper immersion. Content analysis is also perceived as more practical and straightforward, while thematic analysis is perceived as more intuitive and faster to learn. Both content analysis and thematic analysis are perceived to have individual opportunities and challenges that make them appropriate for different types of research. Findings presented in this study can be used by researchers at any level to explore similarities and differences between content analysis and thematic analysis, and where to apply them in research.
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To explore the role of media during mass casualty events and its impact on people.The qualitative thematic content analysis was conducted at Jinnah Sindh Medical University, Karachi, from 2018 to 2020 and comprised of semi-structured in-depth interviews and focus group discussions involving participants from the health sector and policymakers at the provincial level. The Frontline Workers such as the ambulance drivers and the first-aid-givers were also included. Data was subjected to conventional content analysis to generate themes.There were 5 in-depth interviews and 4 focus group discussions in the study. Qualitative analysis revealed that the media has a great deal to do in times of a disaster. The media is the strongest weapon and largely impacts people's mind and behaviour, but it has been playing with their emotions and creating unrest among them.There is a need for the policymakers to set guidelines and define the role of the media in times of a disaster.
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Objective: The objective of this paper is to describe two methods of qualitative analysis – thematic analysis and content analysis – and to examine their use in a mental health context. Method: A description of the processes of thematic analysis and content analysis is provided. These processes are then illustrated by conducting two analyses of the same qualitative data. Transcripts of qualitative interviews are analysed using each method to illustrate these processes. Results: The illustration of the processes highlights the different outcomes from the same set of data. Conclusion: Thematic and content analyses are qualitative methods that serve different research purposes. Thematic analysis provides an interpretation of participants’ meanings, while content analysis is a direct representation of participants’ responses. These methods provide two ways of understanding meanings and experiences and provide important knowledge in a mental health context.
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Qualitative content analysis and thematic analysis are two commonly used approaches in data analysis of nursing research, but boundaries between the two have not been clearly specified. In other words, they are being used interchangeably and it seems difficult for the researcher to choose between them. In this respect, this paper describes and discusses the boundaries between qualitative content analysis and thematic analysis and presents implications to improve the consistency between the purpose of related studies and the method of data analyses. This is a discussion paper, comprising an analytical overview and discussion of the definitions, aims, philosophical background, data gathering, and analysis of content analysis and thematic analysis, and addressing their methodological subtleties. It is concluded that in spite of many similarities between the approaches, including cutting across data and searching for patterns and themes, their main difference lies in the opportunity for quantification of data. It means that measuring the frequency of different categories and themes is possible in content analysis with caution as a proxy for significance.
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This paper is a review of content analysis or thematic analysis which is further explored though the lens of impressions of doctoral students who attended a presentation on the subject.The long tradition of quantitative research still dominates many university courses on research methodology and data analysis. During the 20th century the field of qualitative research has had a growing need for new analysis methods that accommodate qualitative data and two frequently used methods are content analysis and thematic analysis. They have several things in common and sometimes, they have been understood by researchers to be interchangeably. It has been argued by some researchers that conventional content analysis has really the same functional approach to analysing data as an inductive thematic analysis. This study reports on two webinars on qualitative analysis involving doctoral students and facilitated by the authors. The webinars presented, discussed content analysis and thematic analysis, and gathered participants’ reflections on these methods using a Padlet (padlet.com). The aim of the study was to analyse and describe doctoral students' perceptions of content analysis and thematic analysis. The data collected has been analysed using conventional content analysis applying an abductive coding approach. The study identifies several perceived similarities and differences between the two methods, but also opportunities and challenges for applying them. Findings highlight that the two methods are perceived to be applicable to different types of research. Furthermore, they offer similar challenges to the researcher including their potential for bias and could be considered a choice between an intuitive and a practical approach to analysis. Many of the identified perceptions can be related to previous literature on content analysis and thematic analysis. However, other perceptions seems to indicates a need for more thorough and nuanced discussions on methods for qualitative analysis. The study suggest that more efforts should be made to support doctoral students in attaining a nuanced understanding of qualitative methods for analysis.
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The misconceptions researchers have about thematic analysis lead to various problems, which include publishing papers without mentioning the techniques they used to analyze their data. One reason such problems occur is that thematic analysis has been a poorly demarcated method for many years. Another has to do with the lack of literature on how this method differs from other approaches to research. In this paper, I aim to close this gap by explaining how different versions of thematic analysis vary from each other and discussing the controversies associated with each version. My conclusions are based on an analysis of what leading authors have published about this topic. I used a purposeful sample consisting of publications written by notable authors. I then analyzed this content to write a conceptual paper designed to enhance the understanding of different versions of thematic analysis and to document the controversies associated with each type.
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Purpose Although thematic analysis is a commonly used technique, this paper aims to explore the potential advantages (and drawbacks) of both thematic analysis and a dialogic approach to qualitative data analysis. Design/methodology/approach Initially, the epistemology and application of each design, thematic analysis and dialogic analysis are compared. Then, examples of coding segments of narrative data from 85 open-ended interviews with older adults exploring the meaning of place and place-attachment are presented through both thematic and dialogic analyses. Findings The conclusion offers suggestions about how dialogic analysis can add additional context and more participant inclusion and agency to thematic analysis. Originality/value The blending of these two qualitative analysis approaches offers better emphasis on fully presenting older individuals’ narratives.
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Abstract In order to explore and extend our understanding of corporate sustainability definitions and frameworks, we performed a content analysis of a sample of (2013) Fortune 500 companies' standalone sustainability reports using the content analysis tool, Leximancer (http://leximancer.com). Leximancer is a powerful content analysis tool that performs both conceptual and thematic analysis. In addition, Leximancer displays the results of the analyses visually, thus providing a view of the conceptual and thematic structure of the text, and enabling a researcher to quantify and display the text structure. The results of our analyses demonstrate three common themes (Business, Employees and Energy/Environment) observable across eight of the nine industries in our sample. In addition, we observed significant differences in the relative emphasis for the three common themes across industries. We believe a deeper understanding of the themes that motivate firms' sustainability efforts can enhance future research that explores relationships between organizational sustainability efforts and organizational performance.
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