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Using NVivo: An Unofficial and Unauthorized Primer

Shalin Hai-Jew, Author

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What is NVivo?

NVivo is a software tool that complements the work of human researchers working on qualitative and mixed methods (and multi-methodology) research. As such, it enables the ingestion of various types of digital data, the coding of that data, and then various types of queries and analyses of that coding and data. The tool may be used for one part or a few discrete parts of a research project, an entire research project, or even multiple research projects (such as with the same dataset). The tool has a wide range of functionalities, but users may select what features they want to use. 
 



Different "use cases". The software may be deployed in various ways for different types of use cases. The classic use case would involve qualitative and mixed methods types of research, its coding, the analysis of that data, and the output of data visualizations. A highly complex project could be achieved with multiple datasets as different .nvp project files.  For this scenario, NVivo would be used for data management, source annotation, coding, analysis, and data visualization.  

Beyond traditional applications, there may be a use of the tool for parts of a project.  For example, NVivo (with NCapture) may be used to extract a Tweetstream from a Twitter account for content analysis.  It may be used to store all contents of a literature review for easy search and find.  It may be used to create some visualizations for "visual interest" in slideshows and presentations related to particular research. An .nvp (NVivo project) file may be created as a training set for students to practice coding. NVivo may be used to conduct basic exploratory text analyses for digital humanities projects.  


NCapture and Web and social media data.  NCapture, a browser plug-in to recent versions of the Google Chrome web browser, enables the extraction of social media platform data for analysis. This tool enables the capturing of external data from any website on the Surface Web in terms of text and imagery. In social media, it enables captures from Facebook, YouTube, and Twitter. NCapture is part of the NVivo feature set in the Windows and Mac installations.  (The Mac capability was released in Fall 2014.)   [As of Fall 2015, it was announced that Internet Explorer would be discontinued, and the NCapture plug-in feature was not mentioned in relation to IE (whereas it formerly was enabled on IE).  That said, Internet Explorer still exists in Windows 10, even though Microsoft is emphasizing the newer Edge web browser.  To access IE in Windows 10, just search for it in the Search bar at the bottom left of the screen interface.]


Research approach "agnosticism". Ideally, software programs used in research should be theory- and research- "agnostic," which suggests that the tool may be applied in a range of research contexts. Some say that NVivo is reflective of a grounded-theory emergent approach (which begins with data, bottom-up coding of that data, and  informed observations, and ends with post hoc hypothesizing and theorizing and research); others suggest the opposite, suggesting that this software tool benefits an a priori or pre-defined theoretical research approach.  

No matter, how researchers deploy and wield the software tool will affect the research findings.  A software tool should not determine any research approach; rather, the researcher and / or research team should drive the work. The researcher(s) decide when and how software complements human capabilities. Also, the use of the software does not mean that the researchers somehow bypass theorizing or following the research practices in particular academic disciplines, professional fields, or over-arching domains. 

* Sometimes, beginning researchers will reach out and say, "Here is what I did, and I got this visual output. What does it mean?" As with other data analytics software programs, it is sufficiently easy to run a process and acquire a result...but not know what one is seeing, much less how to make a supportable claim from what one has seen.  The following is de rigueur
  1. Know your data intimately (how you acquired it in alignment with IRB support, where it came from/provenance; how it has been handled; how it has been cleaned; known gaps, etc.)  
  2. Know the computational analytics process that you are applying to that data (its strengths and weaknesses) 
  3. Know what is assertable from the findings (and assert no more than you can rationally and reasonably claim...and add considerations for the weaknesses of the assertions) 
  4. Know the reasonable variations on how the findings may be interpreted and viewed, and give other perspectives fair consideration 
Without those fundamental elements, do not make the public assertions in presentations, in messaging, and in publications.   Go with trusted colleagues to review your data and your analyses.   


Going on-paper-and-pen manual or computer-assisted.  Some researchers suggest that the findings that are arrived at through manual coding using butcher paper and pens will differ from manual coding through a computer. This may be so to some degree, but it’s also true that manual coding on paper cannot afford the types of analytics that may be done by machine—which include sophisticated word frequency counts, text searches, and other tools. The computer-assisted version also enables a broad range of data management which is more efficient and accurate than manual-only methods.  


 

NVivo and… NVivo may be used as a complementary tool to a range of other analytical tools. For example, if more sophisticated text analysis, social network analysis, quantitative analysis, or other types of work are required, then additional software should be brought to bear. Some common software tools include the following, some of which are open-source and free and others which are commercial:  
  • Microsoft Visio Professional for diagramming 
  • Adobe Photoshop for image editing and handling 
  • Microsoft EXCEL for statistical analysis and evocative data visualizations 
  • Pajek for graph visualizations 
  • UCINET for graph analysis and basic graph visualizations
  • AutoMap for the extraction of relational data from texts and ORA NetScenes for the visualization of that data 
  • Tableau Public for mapping and the creation of data-rich Web dashboards (there is a for-cost commercial version) 
  • Maltego for Surface Web exploration and data visualizations 
  • SPSS (Statistical Package for Social Science) for statistical analysis 
(Note:  Please read the fine print before making any commitments to any software program. Those in higher education or any sort of accredited educational institution may have access to some pretty impressive discounts.) 

There is nothing to suggest that any research work done in NVivo has to be done exclusively within this tool. (All text, datasets, node queries, and other reports are easily downloadable from NVivo in common file format types.)

There are other software tools that provide some of the similar functions to NVivo but not all and not of a piece. It is beyond the purview of this e-book to cite them. Also, unless the author has had direct experiences with a tool, it would not be fair to elaborate on other tools based on second- or third-hand information.
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