#qualitativedataanalysis — Public Fediverse posts

Reflexivity helps keep qualitative research honest by asking how your background, values, and position shape what you ask, hear, and interpret. It supports ethical awareness, transparency, and trustworthiness by making assumptions and decisions more visible.
Learn more: https://qdacity.com/reflexivity/

#QualitativeDataAnalysis #CAQDAS #Research #QDAcity

Maybe it's a rather far shot but, could anyone out there share their experience using OpenQDA for qualitative research? And has at least comparative experience using QualCoder or MAXQDA/Atlas.ti? ​:neocat_boop:​

Concerning coding text and analysis, usability and reliability. I'm not interested in any of the AI related functionality, just bog standard social sciences qualitative analysis ​:neocat_thumbsup:​.
*Oh, please spare me ye old school recs like using Excel/Word for coding text segments ​:neocat_boop_googly:​.*

Thank you! Boosts appreciated ​:boost:​ ​:Cat_girls_Emoji_003:​

#qualitativedataanalysis #qda #qdasoftware #CAQDAS #socialsciences #sociology #ethnography #fediscience #sciencefedi #phdadvice

A literature review is more than a summary. It helps you map what’s known, what’s missing, and what your study can add. Thematic analysis can support this by coding recurring concepts, organizing literature into themes, refining research questions, and strengthening your theoretical framing with traceable links to evidence.
Explore more: https://qdacity.com/thematic-analysis/

#ResearchMethods #QualitativeDataAnalysis #Research #QDAcity

When interviews aren’t feasible, open-ended surveys can still give you rich qualitative insights. They capture participants’ own words, work well for remote research, and can bridge depth with feasibility. Strong results depend on careful question design, pilot testing, and a clear coding approach.
Read more: https://qdacity.com/open-ended-survey/

#QualitativeDataAnalysis #CAQDAS #Research #QDAcity

I've done minor updates to my list of #FLOSS #QualitativeDataAnalysis tools: https://codeberg.org/stragu/open-source-qda/src/branch/main/README.md
If you know of others, please feel free to suggest edits here or on Codeberg.
#QDA #OpenResearch

Capturing lived experience in qualitative research means going beyond summaries. Thick description adds depth by including participant quotes, detailed settings, and contextual background. It supports validity and transferability, while allowing readers to connect with your analysis. This approach strengthens rigor and offers richer insights into human experiences.
Learn how to use thick description in your research: https://qdacity.com/thick-description/

#Research #QualitativeDataAnalysis #QDAcity #CAQDAS

Uncovering depth in qualitative research requires more than quick interviews. Prolonged engagement allows you to build trust, gather richer data, and better understand context. It strengthens credibility, dependability, and confirmability. More than time, it is about meaningful interaction that reflects real experiences.
Learn how to apply this approach: https://qdacity.com/prolonged-engagement/

#Research #QDAcity #QDA #QualitativeDataAnalysis #PhD #Student

Credibility in qualitative research relies not only on solid data but also on transparency and confirmability. Referential adequacy supports this by encouraging reflexivity, member checking, peer debriefing, and thick descriptions. These strategies help balance subjectivity, reduce bias, and make your work more reproducible.
Learn how to apply referential adequacy in your study: https://qdacity.com/referential-adequacy/

#Research #QualitativeDataAnalysis #ResearchMethods #PhD #CAQDAS #Student

@mediaofcoop Thank you for this report. Your concluding statement regarding AI-supported qualitative analysis is very plausible. This is exactly my impression, too:

"The LLM-led analyses tended to privilege broadly applicable and generalized narratives, often at the expense of interpretive depth, thereby creating an epistemic distance between researchers and the data."

#QualitativeData #QDA #ArtificialIntelligence #LLM #QualitativeForschung #QualitativeSozialforschung #Qualitativedataanalysis

Keeping your coding consistent, especially in team-based qualitative research, can be challenging. A structured codebook helps establish clear definitions, supports shared understanding, and documents analytic decisions. It also contributes to the reliability and transparency of your findings. Frameworks like MacQueen et al. (1998) offer useful guidance.
QDAcity supports structured codebook work: https://qdacity.com/codebook/

#Research #QDAcity #CAQDAS #PhD #QualitativeDataAnalysis #Student

A systematic literature review is more than a summary, it’s a rigorous, replicable method for analyzing existing research in depth.
It helps you identify key findings, expose gaps, and build stronger theoretical frameworks.
QDAcity guides you through every phase, from search to synthesis, ensuring your review is clear, methodical, and credible.
Explore how to strengthen your literature review process: https://qdacity.com/systematic-literature-review/

#QDA #QualitativeDataAnalysis #ResearchMethods #QDAcity #Research

In qualitative research, data triangulation strengthens your findings by drawing from multiple sources, like interviews, observations, and documents.
This approach supports more rigorous, reflective analysis by highlighting consistencies and contradictions across data sets.
It reduces bias and fosters a deeper, more grounded understanding of complex phenomena.
Explore how to integrate it effectively: https://qdacity.com/data-triangulation/

#QualitativeDataAnalysis #Research #ResearchMethods

Open-ended questionnaire responses give voice to participants—offering nuanced perspectives that quantitative data might miss.
Using qualitative analysis, you can systematically code and categorize these narratives, complementing structured surveys and enhancing mixed-methods designs.
This approach helps you move from surface trends to deeper meaning.
Explore how to analyze this data effectively: https://qdacity.com/questionaire-analysis/

#QDAcity #CAQDAS #QualitativeDataAnalysis #Student #Research

So I'm using a CLI-based qualitative data analysis system (it's great! https://qualitative-coding.readthedocs.io) that I integrate into my VSCode workspace. I happened to start experimenting with copilot last week and today when I started qualitative coding I noticed it was offering me suggestions. Seems to be based on my prior codings rather than the actual file from the corpus, but still a bit eerie and not sure if I want to keep this on or not.

#CAQDAS #QualitativeDataAnalysis

Exploring Peer Debriefing in Qualitative Research!
Peer debriefing fosters collaboration and critical dialogue in qualitative research. By sharing findings and insights with experienced peers, researchers refine their interpretations and enhance methodological rigor. Reflexivity is the key, allowing researchers to confront biases and ensure the validity of their work.
https://qdacity.com/peer-debriefing/
#QDA #CAQDAS #QualitativeDataAnalysis #Research #PhDLife

Objectivity is a key dimension along which to evaluate your #research rigor.
While achieving perfect #objectivity might be challenging, striving for it is essential in producing credible and reliable findings. By defining clear hypotheses, following standardized methods, and fostering diverse research teams who contribute through investigator triangulation and peer debriefing, you can enhance objectivity.
https://qdacity.com/objectivity/
#QDAcity #QDA #QualitativeDataAnalysis #ResearchApplication

I've got something really special to share later this week - Episode 11 on my #CAQDASchat with Christina podcast is with the person who has had the biggest influence on my CAQDAS career, one of my very best friends and also one of my co-authors - YES - it's the awesome Ann Lewins.

Watch this space for when this episode drops

#NotToBeMissed #Qualitative #QualitativeDataAnalysis #QDA #CAQDAS #QDAS #QualitativeSoftware #CAQDASchat #DigitalTools #QualAI

Pleased to say one of our most popular workshops is running again in Oct '24.
https://buff.ly/3xPQnxO
Join us for a day discussing the principles of #qualitative data analysis and experimenting with some of the practical tasks involved. This one usually fills up quickly so get in quick. Small groups and two tutors make this a focused, friendly and thought-provoking day. #QualitativeDataAnalysis #QDA #QualitativeResearch #ThematicAnalysis #ContentAnalysis #DiscourseAnalysis #GroundedTheory

@kddk @dennishorn Ich glaube, bei Kommunikation geht es auch um #Gefühle (im hier vorgestellten Fall vielleicht: #Enttäuschung #Unsicherheit) und #Macht bzw #Ohnmacht. Ich finde, das zu #reflektieren haben einige der DiskutantÏnnen stellenweise wirklich sehr gut hinbekommen. Das sind dann auch die Stellen, die sich für mich sehr konstruktiv gelesen haben.

Es wäre m.E. sehr spannend, den hier vorgestellten Thread mal mit Grounded Theory oder Objektiver Hermeneutik anzuschauen.

#GroundedTheory #ObjektiveHermeneutik #QualitativeSozialforschung #qualitativedataanalysis

I love the developer of #QualCoder, an #OpenSource #QualitativeDataAnalysis #software! They are really swift in reacting on github on issues and suggestions for enhancing the software. @sociology @sts @anthropology

See more about the software at https://github.com/ccbogel/QualCoder/

My second question is for partner, not me - does anyone know of *good* open source #QualitativeDataAnalysis software that isn't Atlas? Because she's having relentless issues with #Atlas.

Latest #CAQDASchat #podcast I chat w Stuart Shulman, developer of Discovertext about how he got involved in using computers for #qualitative analysis, methodological dogma, the role of methods/tools & tolerance/flexibility in methods. He explains how Discovertext came about, describes its main tools, and how they can be used for high-quality, rigorous & collaborative analysis of large amounts of data. #CAQDAS #DigitalTools #QualitativeDataAnalysis #QualitativeSoftware https://podcasters.spotify.com/pod/show/christina-qdas/episodes/Christina-chats-with-Dr-Stuart-Shulman--developer-of-Discovertext-e211eke

Two new reviews of #opensource computer-assisted #QualitativeDataAnalysis software (#QDA #CAQDAS):

• In the first review, @VickyRampin presents #QualCoder, #QCoder, and #Taguette in a Webinar:
https://www.youtube.com/watch?v=9teZO-KVwqk

• The second review by #Jess_Hagman is an article comparing #CATMA, #QualCoder, and #Taguette, as well as the free-to-use but non-#FLOSS programs #QCAMap, #QDAMiner:
https://acrl.ala.org/anss/wp-content/uploads/2021/10/2021-fall-anss-currents.pdf (PDF)

#QualitativeMethods #qualitative #ResearchMethods #Research #Methods

In #QualitativeDataAnalysis (#QDA), NVivo is the leading (proprietary) tool. Open Source alternatives are far behind in features, and I feel it is one category of #research tools that is really lacking in the #OpenScience toolbox.

Currently, I would highlight four tools:

1/x

Computer-assisted #QualitativeDataAnalysis Software (#QDA #CAQDAS) is great for text interpretation and #contentanalysis. Besides proprietary software #MaxQDA, #NVivo, #AtlasTi, there are great #crossplatform #opensource packages:

Client:
#QualCoder (inspired by #RQDA)
#Elan
#QCoder (alpha)

Server/self-hosted:
#Taguette
#Cassandre
#CATMA

Special-purpose:
#qdap
#KHCoder
#CLAN

https://en.wikipedia.org/wiki/Computer-assisted_qualitative_data_analysis_software
#ResearchMethods #Research #QualitativeMethods #Methods
#OpenSourceResearch #FLOSSresearch