Qualitative data analysis with hypertext: A case of New York City crack dealers

Ethnography has become a useful method in procuring sensitive information from the ‘hidden population’ who may not be accessed with quantitative survey techniques. Researchers are generating huge amounts of qualitative/textual data. Qualitative data require careful planning in storage, coding, retrieval, and analysis. Personal computers have solved data management problems, but data analysis remains problematic. The paper describes some qualitative data management and analytic problems faced by a team of ethnographers engaged in a longitudinal epidemiological study of cocaine and crack distribution/abuse in New York City. Ethnographic data was collected through multi-session open-ended interviews with more than one hundred cocaine/crack dealers and extensive field-notes were kept. Compared to other programs, a hypertext software — Folio Views — was more useful in solving (a) data management and (b) analytical problems. Authors used this software to handle more than twenty-five thousand pages of texts; search and sort the database by any words or codes; and retrieve relevant textual materials needed to complete comparative and thematic analysis. Authors analyzed the data from outsiders’ point of view (etic) as well as from the viewpoint of the subject populations (emic).     

The evolution of a project involving an integrated analysis of structured qualitative and quantitative data: From N3 to NVivo

Developments in Qualitative Solutions and Research (QSR software) from N3 through to NVivo have impacted not only on the convenience of using the program but also on the capacity of the researcher to undertake interpretive analysis. Perhaps reflective of changes in the broader context of social research, developments through succeeding generations of this software have also increased its capacity to contribute to integrated mixed methods (qualitative and quantitative) analysis. New tools in the software have facilitated bringing quantitative (demographic, categorical and other numeric) data into a qualitative project, primarily to use for comparison of texts across subgroups. In addition, with N4 it has became possible to display tabulated data showing either the presence or absence of coding in particular documents or matrix displays (cross-tabulations) of grouped data. NVivo allows for both greater flexibility and greater specificity of quantitative output. Quantitative outputs from the qualitative database allow for graphical display or statistical manipulation of the data. Numeric output might be combined with existing statistical data to expand analytic possibilities. Interpretation of numeric data is supported throughout by the availability of the text on which such data are based, while patterns in the text can be elucidated through numeric displays. This ability to treat data both qualitatively and quantitatively, using software, can move mixed methods research beyond comparative, convergent or sequential designs toward truly integrated analysis.     

Using natural language processing technology for qualitative data analysis

Social researchers often apply qualitative research methods to study groups and their communications artifacts. The use of computer-mediated communications has dramatically increased the volume of text available, but coding such text requires considerable manual effort. We discuss how systems that process text in human languages (i.e. natural language processing [NLP]) might partially automate content analysis by extracting theoretical evidence. We present a case study of the use of NLP for qualitative analysis in which the NLP rules showed good performance on a number of codes. With the current level of performance, use of an NLP system could reduce the amount of text to be examined by a human coder by an order of magnitude or more, potentially increasing the speed of coding by a comparable degree. The paper is significant as it is one of the first to demonstrate the use of high-level NLP techniques for qualitative data analysis.     

Going the distance: 'Closeness' in qualitative data analysis software

This study about researchers' transitions to using qualitative data analysis (QDA) software identified three stages of 'closeness to the data': the tactile-digital divide; the coding trap; and the metacognitive shift. The 'tactile-digital divide' involves adapting to working on screen instead of paper, an initially distancing process. As users gain comfort with the software, they experience 'the coding trap'--an issue of too much closeness to the data. Users warned that there was a tendency to become 'bogged down' in coding, and developed strategies to provide analytical distance. 'The metacognitive shift' involves learning to think about software processes with the same level of reflectivity that should accompany qualitative research processes in general, including developing strategies for error recognition. These transitions invite reflections on the nature of 'cognitive tools' and expertise with them, which lead to implications for evaluating research and considering trustworthiness.     

Citation analysis and discoverability: a critical challenge for disability studies

Disability is an identity, a culture/community/cause/power struggle; a rights movement demanding civil, ethical, political and social positions at tables of power, equality and social justice. This perspective forms the core of changes in the past 50 years in legal, social and political arenas that have taken place and is essential to understanding the growth, depth and nature of Disability Studies as a separate and legitimate field of inquiry. This study focuses primarily on studying the evolving literature in the core aspects of Disability Studies, using citation and text analyses to study trends in publishing patterns and the field’s impact on the wider academic enterprise. Lack of thorough indexing to key journals made traditional citation analysis impossible, leading to the use of dissertations as a means to tease out useful information on the state of Disability Studies today. The most significant finding of the study is the lack of adequate indexing of key journals in standard scholarly databases, which can only limit the potential development of both the field and its impact/influence on related disciplines and professions. The study also found the significant role that dissertations can play in tracking new research directions.     

Grounded Neural Networking: Modeling Complex Quantitative Data

The latest advances in artificial intelligence software (neural networking) have finally made it possible for qualitative researchers to apply the grounded theory method to the study of complex quantitative databases in a manner consistent with the postpositivistic, neopragmatic assumptions of most symbolic interactionists. The strength of neural networking for the study of quantitative data is twofold: it blurs the boundaries between qualitative and quantitative analysis, and it allows grounded theorists to embrace the complexity of quantitative data. The specific technique most useful to grounded theory is the Self‐Organizing Map (SOM). To demonstrate the utility of the SOM we (1) provide a brief review of grounded theory, focusing on how it was originally intended as a comparative method applicable to both quantitative and qualitative data; (2) examine how the SOM is compatible with the traditional techniques of grounded theory; and (3) demonstrate how the SOM assists grounded theory by applying it to an example based on our research.     

Ethical Considerations on the Use of Archived Testimonies in Holocaust Research: Beyond the IRB Exemption

This paper demonstrates that ethical problems may occur in qualitative research even if it draws on seemingly safe, ??exempt?? data. Drawing on J.L. Jacobs?? concept of ??double vision,?? I describe a number of ethical issues that arose in a project using archived oral Holocaust testimonies; these included concerns about using pseudonyms and identification numbers instead of subjects?? real names and problems with coding the testimonies and writing up the results. Despite these concerns, I conclude that double vision need not always be problematic, and can actually help identify guidelines for producing work that is both scientifically and ethically sound.     

ALL INDUSTRIES ARE CULTURAL

While the conceptual categories of cultural industries and cultural consumption have been useful tools that have yielded valuable insights in a number of studies, they, nevertheless, pose certain problems. This text argues how their usage, in fact, obstructs certain research possibilities. Highlighting the ‘cultural’ character of certain specific industries and forms of consumption can also limit, if not impede altogether, the possibilities of analyzing other industries and forms of consumption from a cultural perspective. Doing away with such categories may open new possibilities for analysis and research. The main focus of this text is the category of ‘cultural industries’ though it also refers in passing to the complementary category of ‘cultural consumption.’     

Word processors for qualitative sociologists: A review essay

Summary and Conclusions To reiterate, we think word processors driven by microcomputers can be used effectively for processing notes, observations and other textual data collected through qualitative research methods and later for analyzing them. Of course, machines cannot analyze data, engender concepts, or write insightful prose. In fact, these machines can do nothing that humans do not instruct them to do. InAnalyzing Social Settings, John Lofland describes the overlap of observation and analysis in a project and suggests the use of a general file structure and mechanical procedures that can stimulate on-going analysis during observation (1971:118). Whatever the system one uses, if the interplay between what is observed and what is made sociologically meaningful can be less a clerical task, then so much the better. In sum, we think word-processing systems can help a sociologist electronically cut and paste raw text files and spur the researcher into producing superior files and reports.     

ICONOCLASM VERSUS INNOVATION: BUILDING A SCIENCE OF FAMILY THERAPY-COMMENTS ON MOON, DILLON, AND SPRENKLE

We dispute Moon, Dillon, and Sprenkle's (1990) claims regarding the unique advantages of qualitative methods and inherent limitations of traditional quantitative approaches for addressing the needs of family therapy research. We support the role of qualitative research as a generative phase in theory development and concur that exclusive allegiance to a standard set of research methods may limit our attention to important family therapy processes. However, we also assert the need to document generalizability of informal observations through controlled procedures using appropriate quantitative techniques. Both ethical and practical considerations demand that we document treatment efficacy based on a science of family therapy.     

A learning collaborative approach to training school-based health providers in evidence-based mental health treatment

Collaborative care models among pediatric primary care and child and adolescent mental health providers are increasingly emphasized to improve quality of and access to mental health services. The current case example of a multi-site clinical training opportunity in school-based collaborative care settings illustrates the success of a learning collaborative approach to improve children's mental health care in schools. Quality improvement data from participating sites indicated an increase in use of evidence-based practices (i.e., “core skills”) and an improvement in quality service delivery indicators for children's mental health (i.e., screening, risk assessment, diagnostic processes, associated diagnostic coding, use of core skills, associated procedural coding, and follow-up assessment and referral) over time. Clinician self-report and chart review data are supplemented by qualitative data from site leader interviews conducted following completion of the project. Implications for mental health workforce development to improve the quality of care to children and adolescents in schools and other community mental health settings are discussed.     

Software and Method: Reflections on Teaching and Using QSR NVivo in Doctoral Research

This reflective paper draws on a range of experiences developed over the last 11 years regarding the way in which qualitative data analysis (QDA) software (QSR NUD?IST and NVivo) is taught and used within doctoral research. The existing separation of qualitative methods training from QDA software training can result in disconnected technical and methodological learning curves. This can cause a number of problems for doctoral students because a ‘methods revolution’ is being experienced and current students are not necessarily exposed to the support they require via the methods literature, their postgraduate training programme or their supervisor. Three key influences on the use of QDA software are discussed within the context of teaching and learning QSR NVivo: the increased popularity of QDA software amongst those from traditionally positivistic backgrounds; the promise of improved levels of transparency; and the reliance upon the free tutorials, which are distributed with the software, to learn qualitative research methods as well as software processes. Implications for doctoral students, supervisors and examiners are discussed.     

Live tweeting and building the digital archive; #NFQLR – who and what is it for?

This paper examines the temporal and ethical affordances of commercial social media platforms, such as Twitter, as tools for engaging in social research and knowledge exchange. Drawing on activity that took place during the New Frontiers in Qualitative Longitudinal Research seminar series, the article reports on using Twitter and other social media platforms to document, share and archive ‘data’ from a series of research events. It also experiments with new modes of research writing, using fragments of ‘data’ from Twitter to distil research knowledge and ideas, whilst also capturing the pace and form of this live method of social documentation and knowledge exchange. Bringing together conversations within digital sociology about how to ‘do’ time in digital research, with methodological debates among qualitative longitudinal researchers about how to research social and biographical continuity and change, the paper argues that the presentist focus in digital research is far from inevitable. Attending to time in digital media demands that we are alert to questions of authorship, audience and co-production, recognizing the labour of research and the provenance of research knowledge, ‘data’ and ideas.