Customizing nvivo 12
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#CUSTOMIZING NVIVO 12 MANUAL#
How to begin manual and/or automated coding various media file types.How to ingest some social media contents.
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How to ingest various multimedia file types (and curate heterogeneous and semi-structured digital data and digitized contents).How to set up a project around a base language (Chinese/PRC, English/US, English/UK, French, German, Japanese, Portuguese/Brazil, and Spanish.How to start and structure a research project (including a team project).The basic parts of the NVivo 12 Plus interface.This presentation, which covers NVivo 12 Plus / NVivo (newest) basics, will address the following: Friday, July 16, for all faculty, graduate students, and staff who may be using this qualitative (and mixed methods, multimethods) data analysis tool. Posted in -Content calendar, -From KSU sources, -To K-State Today, Research and reference Tagged codebook, data analytics, data visualizations, machine learning, NVivo, qualitative data, sentiment analysis, topic modelingĪn “Intro to NVivo” training is scheduled from 1:30-3:30 p.m. If there are questions, please email or call 78. However, K-Staters who want a formal record of their attendance may register via HRIS…or sign up in-person at the online event (and they’ll be credited shortly after the event). Those who have already started using NVivo may want to refer to “Using NVivo: An Unofficial and Unauthorized Primer,” which is an e-book built on the Scalar platform that highlights various features of the tool. QSR International offers video tutorials and both free and for-pay events.
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The subscriptions are for 12 month periods and available for about $99 or so a year. Student licenses are available by subscription for NVivo Windows or the Mac (which has fewer capabilities/features). K-State does not have a site license for NVivo. The presenter will be using the Windows version of the software. How to output a basic report (including a custom codebook).How to set up a qualitative cross-tabulation analysis.How to conduct four types of auto-coding (by extracted themes and subthemes, by sentiment analysis, by structured data, and by supervised machine learning based on existing human coding).How to create data visualizations (word trees, word clouds, dendrograms, ring lattice graphs, sociograms, and others) (for analysis and presentations).How to query the collected data in an NVivo project (word frequency counts, text searches, matrix coding queries, matrix queries, proximity text searches, and other forms of text parsing).