Will you be adding visualization tools like the ones in Optimal Workshop’s Reframer? I have found the chord diagram specifically to be very useful in finding emerging themes as well as to combine themes to find correlated insights.
We don’t have visualization at this time but we’re always looking to add better ways to do qualitative analysis. Thanks for your suggestion and happy to show a demo if you’d like: delvetool.com/demo-sign-up
I personally would disagree with you there. AI can definitely help with certain parts of process and I'm curious how this will evolve over time. But the researcher brings a lot of their own insight and life experience to analyzing data. Two different people will analyze data in two different ways, and to abdicate all meaning-making to AI would imply that there is one correct answer. When in fact both ways can valid forms of analysis. I've played around using AI to analyze data, and by itself it tends to find surface level themes from the data. With some guidance from a human it can be nudged to discover some more nuanced and insightful themes. But a human is still critical to the process. That's my take at least, I'm curious what you have found in your own experience!
![[Webinar Recording] Introduction to Coding Qualitative Data with Delve](http://i.ytimg.com/vi/FMh_2Q2t6kA/mqdefault.jpg)
Will you be adding visualization tools like the ones in Optimal Workshop’s Reframer? I have found the chord diagram specifically to be very useful in finding emerging themes as well as to combine themes to find correlated insights.
We don’t have visualization at this time but we’re always looking to add better ways to do qualitative analysis. Thanks for your suggestion and happy to show a demo if you’d like: delvetool.com/demo-sign-up
Brilliant
Thank you!
I think AI can do this now.
I personally would disagree with you there. AI can definitely help with certain parts of process and I'm curious how this will evolve over time. But the researcher brings a lot of their own insight and life experience to analyzing data. Two different people will analyze data in two different ways, and to abdicate all meaning-making to AI would imply that there is one correct answer. When in fact both ways can valid forms of analysis.
I've played around using AI to analyze data, and by itself it tends to find surface level themes from the data. With some guidance from a human it can be nudged to discover some more nuanced and insightful themes. But a human is still critical to the process.
That's my take at least, I'm curious what you have found in your own experience!