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They can be. Let's say you ask: How do game developers create digital safe spaces for female gamers?, then a handful of themes that describe how these safe spaces are created can be a great answer to the RQ. But themes do not have to be the exact answer to a RQ. They can simply be the result of conducting the method of thematic analysis which is part of a larger study with a broader or multiple RQs. Best of luck!

My pleasure!

I'm glad you liked it. :)

Great question! If the study is for a greater good and privacy measures are taken such as pseudonymization, the analysis of such data for research purposes can be done ethically without asking for consent first (it would be impossible). It is possible to transparently share what has been done in the study and what data has been used for what. This is to „inform“ without the „consent“ so to speak. It can be done on a public website of a researcher, uni, or project. But most researchers don’t do that. What helps would be to apply for an ethics approval at your university for your specific case. I think labelling a large-scale analysis a netnography is not exactly in line with the original idea. I would label it social media analytics. You can also search for papers on research ethics in netnography and social media analytics to get more ideas about what ethical considerations would be most appropriate for your study. There are papers that discuss both. Best of luck 🤞 Phil

You're welcome! Thank you for commenting.

Thanks! 🙏

Cool! I’m glad to hear that 👌

You can also do it step by step. At the open coding stage (first level abstraction) in any qualitative method it doesn’t matter if you do it step by step or all at once. It might be even better because you can make sure that the AI does not skip any transcripts. Pls also delete any names and company information before entering transcripts in ChatGPT. Best of luck 😊👍

@@masteryourstudies Step by step meaning put in one transcript at a time? Or put in the corresponding passages of each transcript together?

Thank you for your comment. I am not sure if I can answer your question without knowing more about the context, research question, and so on. You can definitely derive practical implications such as recommendations to managers but make sure you also tackle a research problem (i.e. a theoretical problem or important research gap). Best of luck! 🤞

I’m working on more videos on grounded theory 👍

😃

That‘s great to hear 👍 let me know if you have questions. Best wishes, Phil

Hi, you can ask me anything :) Yeah, I don't want you to get in trouble so when you use AI, please always disclose in your methods section how you used it. It is possible to use AI tools and many software tools for qualitative coding already have AI-powered plugins to support with coding. My take is that AI can be a great help on the first level of abstraction. This means assigning codes to a large body of text or other data. In principle, this part of thematic analysis and any other qualitative method is pretty mechanistic and does not require a lot of creativity - so its perfect for AI. Once you get to the higher levels of abstraction - in this case themes, I would move away from the AI and interpret the codes yourselves to create something new. The disadvantage if you use AI in the coding stage is that you do not familiarise yourselves with the data and this will make it harder to interpret it later. If you want to dive deeper into how to use AI I made a tutorial about ChatGPT and qualitative data analysis: th-cam.com/video/CvCdERtCoC8/w-d-xo.html best of luck! :) Phil

@@masteryourstudies Hello, thank you for your reply, my problem is that I am currently writing a memory (for my last years master in psychologie) with a qualitative analysis. I have 4 semi-structured interview groups of 6 each, which makes 24 interviews to analyze separately. I'm afraid that during my re-reading I won't be able to find the codes and themes easily. I find myself a bit lost and it's stressing me out, hence the AI question, as it seems more precise to me. What do you think? Many thanks

@@masteryourstudies In my semi-directive interview, I have 8 questions and each subject answers in a different way. I'm afraid I'll end up with a lot of codes, so what can I do? Is there a code-sub-code hierarchy system? Thank you for your answer.

Thanks! For TA it is sufficient to refer to codes and themes. Sometimes different authors use different labels although it is the same. The first method I Iearned was qualitative content analysis, where codes are „categories“. But Braun and Clarke don’t use that term so I would stick to the vocabulary that is used by the authors that you cite for a particular method. Best wishes, Phil

Thanks!! 🙏

Hi, thank you for your question. If you use predefined themes, you are using thematic analysis with a deductive (i.e. top-down) logic. Here, you can derive themes from an existing theoretical framework, for example. You can develop some additional themes or subthemes inductively (i.e. bottom-up) but then you are mixing two logics and need to be very deliberate in what you are doing. I would not advise you to take themes from your research questions - this is not exactly what the method intends to do. Have a look at the Braun and Clarke papers, they give great examples and then it will „click“ for you :) best of luck 🤞

Hey, thanks for your question. Your research question(s) and themes are two different things. You could keep the RQ(s) and then develop themes that are barriers and drivers etc. but those should not be coding buckets as I explained in the video. This would lead to having "a digital mindset" and "risk tolerance for innovation" (just random examples) inside one coding bucket - but what you want to do with the method is develop them as independent themes (with concrete data examples and subordinate codes for each). That's why these buckets should be avoided. One way to avoid asking about "disadvantages" and "advantages" etc. in research questions is by changing the question to a "how" question: th-cam.com/video/hB-BS1xDU2M/w-d-xo.html Best of luck! :-) Phil

Thanks for your support!! 😁👏

Please have a look in the video description, where I cite their 2021 update. The video is based on the original paper as well as the update from 2021. Best wishes :-)

I see that, but nevertheless I would recommend not using the 2006 paper as a reference anymore, but base the analysis on the 2022 textbook Thematic Analysis: A Practical Guide (Sage).

Yes you would need a local instance of GPT or another LLM

It's possible to sanitize/anonymize the data before entering it, that way you do not in put PII or confidential data

Hi Anna, thanks for your comment. I'm glad the video could help you a little bit. It depends on your research design. If you combine a (systematic) literature review and your interviews as your method, then I would analyse both separately with TA and report the results separately as well. Then merge what you found in the discussion. If you do a non-systematic literature review that is not part of your research design, then only analyse your interview data with TA and write a strong background section based on the literature you have collected and read. Best of luck! Philip

Thank you so much, I'm going to do the last one you proposed. 🤗 @@masteryourstudies

I am using codes/nodes through NVivo and approaching a topic from a constructionist point of view

Thanks for your comment. This will be a niche tutorial but I will give my best to cover it at some point. Producing these takes time, so in the meantime don't hesitate to ask specific questions here in the comments. Best of luck! Phil

Hi Paul, thank you for commenting. I will do more videos on coding but these videos take time… Strauss and Corbin is a bit more concrete in its coding guidelines, so most students like this better than e.g. Glaser (1978). I suggest you work really closely with the book. There are also some videos on TH-cam that show example codings, which might help you. My last tip is getting the book Grounded Theory for Qualitative Research by Cathy Urquhart. It explains in easy language the difference between all these approaches and has great examples. Best of luck! Phil

@@masteryourstudies hey Phil :) Thinks! By any chance… do you do 1:1 advice teaching sessions?

Hi, thanks for your question. In a deductive approach, you would have your themes predefined by existing literature and/or theory. Nothing wrong with theses "buckets" here, but you need a good justification and enough literature that back these up. In inductive TA, buckets are more problematic because the interpretative element gets lost. You want a theme that represents the data and not a label that groups them. Best of luck!

Thanks for taking the time to reply, it makes sense! @@masteryourstudies

Thank you! ☀️

Hi Sabrina, thank you for your question. Generally, I would choose one particular approach to grounded theory and then stick to it. This could be Gioia et al. (2013) or Glaser (1978) or Strauss and Corbin (1998) or Charmaz (2014) and so on. The Gioia method speaks about coding techniques that are equivalent to open coding and axial coding for example. These are just labels for different steps of the method and different authors use different labels. So when you do the Gioia method, you automatically do open coding and axial coding, it is just called differently in the Gioia et al. paper. But generally I would not mix too many authors, their suggestions, and labels. Stick to the one Grounded Theory guideline that resonates with you most and serves your purpose well (your research objective). Best of luck! Philip

Good luck 😊👍