Mac and Linux-based qualitative researchers have a potential new tool available to them in dedoose, a multiplatform browser-based system for coding and analyzing qualitative data. It makes dealing with data on any platform pretty straightforward, and was built for big teams. All data and analysis occur online, making projects easily accessible to many users working from nearly anywhere with an internet connection.
That said, my initial experiences with dedoose (a name that makes me cringe whenever I have to type it), weren’t great. One reason I love ATLAS.ti for qualitative analysis is that it handles a broad range of file types; specifically, it allows you to code directly onto pdfs without a hitch. Dedoose wasn’t too crazy about loading the pdfs of 1960s newspaper articles that I’m working with. As a historical sociologist, this is pretty crucial for my work, though it’s much less important for most qualitative researchers. Additionally, the dedoose web app crashed when I tried to load Word .doc and .docx files. While it’s easy to convert these into .rtf or plain text files, it’s a frustration, especially considering dedoose’s claim that it supports these file types natively. Its user interface also feels a bit stiff and outdated, though aesthetics admittedly are never the first thing you look for in research software. Continue reading “Browser-based qualitative data analysis – dedoose”
Melanie Jones Gast, an assistant professor in DePaul’s Department of Sociology, talks with the SSRC’s Julian Thompson and Frank Edwards about her research on the impact of community-based organizations on young immigrants’ access to resources in the San Francisco Bay area. She discusses why qualitative research methods are particularly useful for identifying how social institutions structure young people’s lives.
Robyn Brown, a sociology professor at DePaul, is conducting research to assess how different social groups deal with the stresses of living in a recession and what explains the differences in tension-reducing behaviors between groups. She’s using structural equation modeling to assess how multiple stress-related behaviors are related to each other in a more intricate way than regression modeling allows. SSRC Research Assistants Frank Edwards and Julian Thompson chatted with Robyn about her research.
DePaul’s sixth “ethnographilm” festival will feature ethnographic, documentary film shorts, each produced in roughly five weeks by DePaul students from Ethnographic Documentary Film Production, a class taught by Dr. Greg Scott, a film/audio documentarian, associate professor of sociology, and director of the Social Science Research Center at DePaul.
Here’s a review of what jump/cut was like last year.
Jump/cut ethnographilm festival #6 Monday, June 4
DePaul University – Lincoln Park Campus Schmitt Academic Center (SAC) Room 254 – 2320 N Kenmore
Kristen Miller, the director of the CDC’s Question Design Research Lab, will be at DePaul next week sharing her survey know-how with anyone who wants to learn more about how survey research on a grand scale operates on the ground. Check out the schedule below and join us at the SSRC for a promising display of survey and methodological insights and derring-do.
Friday, February 10, 1 pm: Faculty Seminar
“Development and Evaluation of a Sexual Identity Measure for the National Health Interview Survey (NHIS)” Miller will describe the use of qualitative research in developing a precise sexual identity measure for a large-scale quantitative survey and the resulting complications.
Monday, February 13, daytime: Lab Visits Faculty are invited to schedule appointments to meet with Miller to discuss their research, questionnaire design, or other research questions.
Monday, February 13, 6 – 7:30 pm: Public Lecture
“Question Evaluation at the National Center for Health Statistics” This lecture, open to the public, will center on Miller’s work at the CDC and will consider examples of questions that inadvertently compromised data quality through a lack of rigorous evaluation.
I talked with Kristen today to learn more about what she does and why it matters.
We just finished up training a group of DePaul faculty and students this morning in the use of ATLAS.ti, an incredibly flexible and powerful tool for qualitative data analysis, and it occurred to me that it might be helpful to put together some resources that are useful for doing one type of (generally) qualitative research. Content analysis, a system for analyzing patterns in textual data, is a perfect method for evaluating structures in large samples of relatively uniform texts. However, many folks aren’t clear on exactly what content analysis is, or how it differs from just reading a group of texts and inferring meaning from them. Content analysis applies particular tightly framed questions to a clearly defined sample of texts.
How might we quantify, much less visualize, the networks that control the flows of global capital? While sociologists, political scientists, historians, economists, and many other scholars have long known that global finance is controlled by a handful of organizations and individuals, there were few ways to effectively map out the networks that control global speculative markets. Until now.
A team of Swiss “econophysicists” has developed an intricate network analysis that provides empirical support for claims about the disproportionate and overwhelming power falling to a small number of international firms. In fact, their analysis finds that ten firms in particular wield incredible power in world markets, shedding illusions that markets are controlled by vast groups of people and organizations.
Moving beyond a simple analysis with identified nodes, these scholars built a model to account for the dynamic and varied influence of organizations under changing market conditions, the power gained by intermediaries, and the structures of corporate ownership. By both quantifying and visualizing the nodal relationships between actors in stock markets, this team lends substantial empirical support to what many scholars have understood for quite a long time.