r/QualitativeResearch

AI is now being used for transcription, coding, summarisation, desk research and even interview planning.

But has it changed the way researchers actually work, or is it mainly helping with the time-consuming parts?

Would be interested to hear what has genuinely worked for you, and where you still prefer the traditional approach.

doing research interviews rn and half my participants switch between english and french/spanish mid sentence. every tool i tried just gives up or outputs total gibberish when they code switch like that. is there anything that actually handles multilingual transcription without me fixing everything by hand after? student budget so nothing crazy expensive pls

I’ve been thinking about how much of market research happens outside the actual research itself.

For those working in qualitative or mixed-methods research, what part of your workflow tends to take the most time?

Is it:

• Recruiting and scheduling participants
• Conducting interviews or focus groups
• Transcription
• Coding and organizing data
• Finding patterns across responses
• Synthesizing findings
• Writing reports or presentations
• Something else entirely?

I’d be interested to hear what takes up the most time for you and whether that has changed over the past few years.

PS: it's not a survey.

Hi everyone, just a friendly reminder from the mod team about an important event next year for our community: if you’re planning to submit to ECQI 2027 (European Congress of Qualitative Inquiry), the abstract deadline is September 9, 2026, and it’s now only a few weeks away.

The congress will be held January 12-15, 2027 in Seville, Spain, hosted by the University of Seville.

You can find the submission details here: https://ecqi2027seville.es/

Hi all. I am an undergraduate student who is quite behind on her thesis seeking advice about qualitative framing analysis for newspaper articles (comparing a chinese concept in anglo-american/chinese-based english media, the guardian/nyt vs china daily/global times). I am fundamentally quite confused about the process of how to code for frames in the newspapers as I fear I have gone into a large spiral of overthinking and overcomplication. I am doing this manually and solo-coding (I had a late topic change and significant mental disruption during the first half of this year and essentially have three months left til my submission with nothing concrete on paper yet, so please excuse my lack of progress).

I plan to do a combination of deductive and inductive frames, building on generic established frames like semetko/valkenburg's and then adding in a few china-specific ones, followed by any inductive ones that arise. But my main concerns are as following;

1. How to properly code for frames? is it simply just creating operational definitions and questions to guide frame identification (borrowing from the deductive pre-existing and adapting to issue-specific inductive ones)? I think here I am getting indicators quite mixed up and confused, and in building a coding framebook I am also quite lost.

2. What is being recorded in framing analysis? is it just frames per articles/tiers themselves, or every extract used to justify the frames?

3. How big is too big for a corpus? If I roughly have around 65 articles identified for one tier and more for the other tier, is it best to size down - systematically random sample to make the corpus smaller?

TL:DR Any advice or generic help to clarify framing analysis would be much appreciated!!!