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witman

Peer-reviewed or other validation of thematic auto-coding?

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witman    1

I'm writing a paper using some textual analysis done by Nvivo's auto-coding using themes. Is there a peer-reviewed (or QSR-written) paper that verifies the validity and quality of Nvivo's analysis using this technique? I found Andrea Goncher's paper called Using automated text analysis to evaluate students’ conceptual understanding from the Proceedings of the Australasian Association for Engineering Education (AAEE2014), but it's about Nvivo 10, it doesn't claim very high levels of validity. I'm hoping that either QSR has done a study of the theme-based auto-coding in Nvivo 11, or that you can point me to another source.

 

I asked this question of QSR support also, but thought this community might have an answer.

 

Thanks,

Paul Witman

witman@ieee.org

Assoc. Prof., IT Management, California Lutheran University School of Management

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dstoneky    1

Good question - to which I'll add a corollary. Can QSR provide more description about this process? What is the specific modeling process used here? I'm guessing this is a form of cluster analysis but more description is essential to a transparent process that can be validated and triangulated against other automated coding models.

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I've been looking out for similar info on the autocoding process lately and the only description of how the thematic coding works I've been able to find is in the Nvivo manual here: http://help-nv11.qsrinternational.com/desktop/concepts/how_auto_coding_themes_works.htm. This identifies that the process as per text pasted below and then explains a little further.

Anyone found any other assessments (peer reviewed or otherwise?) of the autocoding process yet?

Having used it myself for a couple of months now it seems to find all the things I would search for myself (and a lot I don't need, but that doesn't matter) and seems to just save doing a lot of frequency and text queries rather than addling loads more smarts or anything like artificial intelligence yet (here's hoping for AI one day...).

Cheers,

Elizabeth G

 

What makes a theme?

The process detects significant noun phrases (for example, real estate development) to identify the most frequently occurring themes.

The process collects the themes and counts their mentions across all sources in the set being processed.

NVivo actively filters the themes—only the most relevant themes are presented in the results. You can choose which themes to create as nodes at the end of the process.

The automated insights process may produce different results in different languages. For example, if you have a translated version of the same source, analyzing the French version in French and the English version in English may produce different result

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