MN5456: Data Analysis of Interview Transcripts Using NVivo

This project focuses on qualitative data analysis using NVivo software. It begins by importing interview transcripts into an NVivo project. The core of the assignment involves creating codes for the selected interviews, followed by generating a word frequency query to visualize the data using word c...Read More

Data Analysis

Table of Contents
1. Project Description...........................................................................................................1
2. Creation of NVivo Project................................................................................................1
3. Code Creation...................................................................................................................3
4. Mind Map..........................................................................................................................7
5. Export the Nodes.............................................................................................................15
References...............................................................................................................................18

1. Project Description
The main objective of this project is to select the eight interview forms’ provided
interview transcripts and upload them into the NVivo projects. Later, it requires creating code
for the selected interviews in NVivo followed by creation of Mind map, and provide the
explanation of the created node hierarchy. At last, export the top three nodes ranked by
number of references (AlYahmady and Al Abri, 2013).
2. Creation of NVivo Project
First, open NVivo (Brandão, 2014).
Click on the Data tab to Documents and select the provided interview transcripts as
shown below.
1

To import the provided interview scripts click on OK as presented below (Edwards-
Jones, 2014).
The provided interview transcript is imported successfully as presented below.
2

Afterwards, select the eight interviewers as displayed below.
3. Code Creation
Create code for the selected eight interviews by right clicking on the selected
interviews, and click on Code as represented below (Leech and Onwuegbuzie, 2011).
3

Then, enter the node name as Interview and click on the Ok button as demonstrated below.
The code is created for the selected interviews as displayed below.
4

Next, run the created code by clicking on query tab to choose the word frequency as follows
(Park, 2012).
Click on Run query, and it will provide the output for the created code as you can see in the
below screenshot.
5

The output is presented in the form of word cloud visualization, and is demonstrated below.
The output is also presented in the form of tree map visualization as follows (Spencer, 2015).
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4. Mind Map
Create mind map for the selected eight interviews by clicking on explore to choose
the mind map and enter the labels. The created mind map is illustrated below.
Also, create hierarchy chart for the interview node by clicking on explore to choose the
hierarchy chart, which is used to provide a detail view of the node hierarchy, and it emerges
the interview details. To create a hierarchy chart, select visualization as a node and click on
next (Zamawe, 2015).
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Select the node and coding as all nodes and click on Finish button.
The hierarchy for the interview node is presented below.
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The summary of the hierarchy chart is presented below.
A node hierarchy of the created interview mind map is used to provide an effective
analysis of quantitative interview data analysis. The node hierarchy of the selected eight
interview mind map is based on word, length, count and weighted percentage. And, it is used
to present the structure of the mind map and story line of the selected eight interviews, which
is presented below.
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Word Length Count Weighted Percentage (%)
2020 4 1 0.32
academic 8 1 0.32
accounts 8 1 0.32
actually 8 1 0.32
affect 6 1 0.32
afraid 6 1 0.32
ahead 5 1 0.32
always 6 1 0.32
amount 6 1 0.32
another 7 1 0.32
anything 8 1 0.32
ask 3 1 0.32
available 9 1 0.32
bit 3 1 0.32
broadcast 9 1 0.32
business 8 1 0.32
caused 6 1 0.32
celebrities 11 1 0.32
chat 4 1 0.32
children 8 1 0.32
colleagues 10 1 0.32
community 9 2 0.65
contact 7 1 0.32
contacts 8 4 1.29
cooperation 11 1 0.32
daily 5 3 0.97
data 4 1 0.32
depending 9 1 0.32
develop 7 1 0.32
different 9 1 0.32
differentiate 13 1 0.32
discovered 10 1 0.32
10

dissertation 12 2 0.65
done 4 1 0.32
easy 4 1 0.32
embarrass 9 1 0.32
emoji 5 1 0.32
emotions 8 3 0.97
enjoyed 7 1 0.32
etc 3 1 0.32
every 5 1 0.32
exactly 7 1 0.32
examples 8 1 0.32
excited 7 1 0.32
experiences 11 1 0.32
express 7 3 0.97
extant 6 1 0.32
family 6 6 1.94
Far 3 1 0.32
followers 9 1 0.32
friend 6 1 0.32
friends 7 4 1.29
friendship 10 1 0.32
give 4 1 0.32
group 5 1 0.32
groups 6 1 0.32
hand 4 1 0.32
happy 5 1 0.32
hear 4 1 0.32
hearing 7 1 0.32
hello 5 1 0.32
hesitate 8 1 0.32
highlight 9 1 0.32
hours 5 2 0.65
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husband 7 1 0.32
improve 7 1 0.32
incidents 9 1 0.32
individuals 11 1 0.32
information 11 3 0.97
interact 8 2 0.65
interaction 11 1 0.32
interview 9 1 0.32
interviewee 11 15 4.84
interviewer 11 17 5.48
joined 6 1 0.32
lastly 6 1 0.32
learning 8 1 0.32
library 7 1 0.32
like 4 1 0.32
live 4 1 0.32
london 6 1 0.32
make 4 1 0.32
manage 6 1 0.32
media 5 7 2.26
meet 4 4 1.29
meeting 7 3 0.97
message 7 1 0.32
messaging 9 1 0.32
minutes 7 1 0.32
mom 3 1 0.32
morning 7 1 0.32
mostly 6 1 0.32
mrs 3 1 0.32
much 4 1 0.32
negative 8 3 0.97
network 7 1 0.32
12

new 3 2 0.65
news 4 2 0.65
nice 4 2 0.65
official 8 1 0.32
often 5 1 0.32
One 3 1 0.32
part 4 1 0.32
particular 10 1 0.32
partners 8 1 0.32
people 6 2 0.65
peruse 6 1 0.32
physical 8 1 0.32
platform 8 3 0.97
platforms 9 6 1.94
please 6 1 0.32
pleased 7 1 0.32
positive 8 3 0.97
privacy 7 1 0.32
private 7 2 0.65
process 7 1 0.32
professional 12 1 0.32
public 6 1 0.32
purpose 7 2 0.65
questions 9 2 0.65
rank 4 1 0.32
really 6 1 0.32
regarding 9 1 0.32
related 7 1 0.32
relations 9 2 0.65
replace 7 1 0.32
schedule 8 1 0.32
See 3 1 0.32
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select 6 1 0.32
sent 4 1 0.32
Set 3 1 0.32
settings 8 1 0.32
share 5 2 0.65
snap 4 1 0.32
snapchat 8 3 0.97
social 6 9 2.90
sometimes 9 1 0.32
sons 4 1 0.32
specific 8 1 0.32
spend 5 1 0.32
start 5 1 0.32
surgeon 7 1 0.32
taking 6 2 0.65
talk 4 2 0.65
tasks 5 1 0.32
Tell 4 1 0.32
terms 5 1 0.32
text 4 3 0.97
thank 5 2 0.65
thrilled 8 1 0.32
time 4 5 1.61
today 5 2 0.65
told 4 1 0.32
touch 5 1 0.32
transcript 10 1 0.32
Try 3 1 0.32
tweeter 7 3 0.97
twitter 7 1 0.32
two 3 1 0.32
Use 3 10 3.23
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using 5 3 0.97
Via 3 2 0.65
video 5 1 0.32
voice 5 1 0.32
well 4 1 0.32
whatsapp 8 6 1.94
whether 7 1 0.32
work 4 5 1.61
Yes 3 2 0.65
5. Export the Nodes
At last, export the created nodes by clicking on the Nodes.
Next, right click on Nodes to click on Export (Swygart-Hobaugh, 2019).
15

Select the export view as reference and Ok button to export the Node as demonstrated
below.
The export node is presented below.
16

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References
AlYahmady, H. and Al Abri, S., 2013. Using Nvivo for Data Analysis in Qualitative
Research. International Interdisciplinary Journal of Education, 2(2), pp.181-186.
Brandão, C., 2014. P. Bazeley and K. Jackson,Qualitative Data Analysis with NVivo(2nd
ed.). Qualitative Research in Psychology, 12(4), pp.492-494.
Edwards-Jones, A., 2014. Qualitative data analysis with NVIVO. Journal of Education for
Teaching, 40(2), pp.193-195.
Leech, N. and Onwuegbuzie, A., 2011. Beyond constant comparison qualitative data
analysis: Using NVivo. School Psychology Quarterly, 26(1), pp.70-84.
Park, C., 2012. Analyzing qualitative data with the aid of computer-based software program
(NVivo 9). Journal of the Korea English Education Society, 11(1), pp.203-222.
Spencer, C., 2015. ‘Qualitative Data Analysis with NVivo’ Pat Bazeley, Sage Publications
Limited, 2007. Australasian Journal of Paramedicine, 5(3).
Swygart-Hobaugh, M., 2019. Bringing method to the madness: An example of integrating
social science qualitative research methods into NVivo data analysis software
training. IASSIST Quarterly, 43(2), pp.1-16.
Zamawe, F., 2015. The Implication of Using NVivo Software in Qualitative Data Analysis:
Evidence-Based Reflections. Malawi Medical Journal, 27(1), p.13.
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