Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
November 2nd 2010
Wiki Comments and Advice
Last week’s Wiki was comprehensive but had some issues with clarity. It is important for the
class to remember that during weeks with a dense amount of material clarity is important. Here
are a few pieces of advice to remember when writing a wiki:
1) The wiki needs to be an standalone document
2) Outside reader needs to be able to read the Wiki page and be able to understand the
material.
3) Avoid cryptic comments, being brief is important but you need to maintain a clear focus
with information you present.
4) Be clear in your definitions to ensure sentence clarity.
5) You can refer to other material for greater detail on a topic, but the topic itself must be
complete and standalone document.
6) Typos happen, but you need to be thorough in your editing because it influences readers
perception.
Data Collection
Data collection methods include:
1)
2)
3)
4)
Interviews
Documents
Observations
Surveys
Content Analysis
The use of objective and systematic counting and classification procedures to produce a quantitative
description of symbolic content in a text.
Content – words, meanings, pictures, symbols, ideas, themes, or any message that could be
communicated
Text – anything written, visual, or spoken that serves as a medium for communication
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
Framework
Typically this method is used in a positivistic or post-positivistic framework.
This method is most common in evaluating large amounts of information and often results in the attempt
to make large generalizations to the whole population.
One of the main aims of this method is to create a process of research that can be easily replicated by
other researchers.
Computer programs are now are available which can perform certain aspects of content analysis. These
programs can be set to search for certain phrases or words in a selection of samples.
i.e Twitter Trend analysis is a very basic form of content analysis.
Conducting Content Analysis
1) Choose a unit of analysis – this could be an entire article, paragraph or even single line in a
document.
2) Create a coding book – this should contain your coding framework. Establishes what variables
you are assessing and how you are assessing them. Important to ensure your variables are
mutually exclusive.
In Class Example:
a) News Anchor
a. Male or female
b) Reporter
a. Male or female
c) Expert
a. Male or female
In Class Exercise
With the provided handout students must watch the following news stories and fill out the
information in the table provided. The goal of this analysis is to answer the question:
Are men associated with hard news stories and women associated with soft new stories?
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
Two sets of news stories are were shown
CBC
1) Researchers have found concussions in sports, focused on hockey, are more prevalent and
dangerous than previously understood.
2) Recent studies have labeled alcohol are more dangerous to society then hard drugs such
as crack cocaine or heroin
3) Ashley Smith’s is calling for more investigation into her death in federal custody, which
was designated a suicide.
CTV
1) After the bomb threat from Yemen Canada has joined most European countries and the
United States in banning air cargo from Yemen. Cargo package screening process is now
be revised.
2) Omar Kadhr trial has resulted in the agreement that he will spending the remaining part
of his term in the Canadian penitentiary system
3) US midterm elections indicate a strong surge in Republican support in the United States.
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
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Class found that in areas where the variables were clearly outlined, male or female,
anchor or news reporter, there was general consensus.
In more vague areas open to interpretation (expert/not expert or hard vs. soft news) there
was less consensus.
Strengths
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Similarity of results from replication are high
Little training is required for researchers to achieve accurate results
Process is transparent
Rigorous (categories are precisely defined)
Reliable (measures are applied consistently)
Replicable (the project can be replicated by another researcher)
Weaknesses
-
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Measurement is difficult
o Hard to count what is not included (narrow focus)
o Dealing with frequency, replication, intensity
Does not address concerns about validity of text
Not everything that counts can be counted
o Neglects to address context
Thematic Analysis
Reading: Richie and Spencer post-positivist approach thematic analysis
Their approach was structured steps:
1)
2)
3)
4)
5)
Data is reviewed
A thematic framework is identified
An index is created and applied to the data
Summaries of data are entered into a chart
These summaries are charted and brought together
Exercise
Use handout to read through the interviews and research question. Make notes on key points and
themes within the interview and any points that relate to the research question. Go through the
following steps:
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
1) Identify a thematic framework
Below are the handout instructions for building a thematic framework.
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-
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Read back over the original research question and the question in the topic guide.
Read over your notes and attempt to identify some key issues, concepts and
themes according to which you think it will be possible to examine and reference
the responses to this question in all the interview transcripts.
Create a draft index that you can use to code the transcripts. Use figure 12.2 from
the reading as a guide.
Try applying your index to one or two transcripts. In the process of doing this you may
find that your index does not fit as well as you thought it would. Make any necessary
revisions to your index.
Now get back into your groups and compare your indexes. Create a single index
for your group.
Now try applying your revised index to a couple more transcripts. If you have any
problems get back into your group and make necessary revisions. When you are
reasonably happy with your index you are ready to move onto the next step
(indexing).
2) Indexing
Assign a transcript to each group member and use your index to code the transcript
excerpts. Use 12.3 as a guide to what this looks like. If you are using coding software
such as N’Vivo you would carry out this step using your software.
Possible indexes for this example:
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-
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Beneficial for parents
o Increased parenting knowledge
o Socialization for parents (avoid loneliness)
o
Beneficial for kids
o Self esteem
o Respect/pride
o Learning
o Time
o Disability
o age
Social Benefits
o Societal value
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
o
Program assistance
Hand out example:
3) Charting
- Create a thematic chart including:
o Interviewee ID
o Agency ID
o Type of agency – profit or not-for-profit
o Type of agency – disability or mainstream
o Type of agency – religious or secular
- The next sections on the chart to be determined by group based on their indexes.
Examples of categories are:
o Benefit for children
o Negative effects for children
o Benefit for parents
o Negative effects for children
o Societal benefits
-
Why synthesize info into a chart after the index?
o It is a reference point, simplifies data available
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
o
o
Allows you to return through your chart, and index to find details afterward
Chart should indicates patterns (i.e. benefits to parents, children)
4) Mapping and Interpretation
Bring together all parts of the chart into summarized categories. Class discussion ran out
of time to cover final step. Figures 12.6-12.9 in the Richie and Spencer article are
examples.
Strengths
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Data analysis process is clearly defined and can be explained
Process is reliable and replicable
Weaknesses
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Analysis risks being too reductive
Themes are considered in isolation of broader social context
Issues of power not explicitly considered
Grounded Theory
Activity was provided but due to time limits it was not possible to complete it in class.
Grounded theory was developed by Glaser &Strauss: The Discovery of Grounded Theory in
1967.
The aim is explicitly designed to be grounded in peoples experiences.
o
o
o
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A hermeneutic approach
Desire to understand subjects world view
Much more structured then most hermeneutic research
 Greater focus on systematic research
o Key steps are set out
 Open, - breaking up and fragmenting data for examination
 Axial - looking to establish relationships among categories created.
 and Selective Coding – trying to establish a storyline, answer to the question
o A lot fewer steps then thematic analysis
Strengths
o Less reductive
o Data analysis more flexible but maintains clarity
Weakness
o Supposed to be w/o a theoretical lens, yet not clear if this is possible
o Themes considered in isolation of broader context
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
o
Issues of power not considered
 Trying to understand the world view of group
 Not studying why they speak the way they do or why they remain silent on the
topic
Post-structuralist discourse analysis
What is discourse?
“System of statements which constructs an object” (Parker)
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Language allows us to understand, also frames our understanding
Discourses are “practices that systematically form the objects of which they speak” (Foucault)
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Discourses involved power and knowledge
Rejection of simplistic causality
Denial of inevitable and linear historic progression
Concerned with relationships about power, knowledge and language
i.e EES reading is example
o EU documents and writings create a problematic in their discourse that policy makers can
act on
 this leads to subjectivities
 changes the way we think about ourselves
 i.e remaining active, being flexible, not getting attached to a single
position
No text yet exists that outlines systematic steps of the process. If you can find one let Prof. Brady
know!!
Strengths
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themes are not isolated
issues for powers are accounted for
least reductive approach
Weaknesses
-
process can be unclear
not suitable for positivistic research
difficult to communicate
Week 9 Lecture Notes – Qualitative Data Analysis Eric
Rines
Summary
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Range of approaches to qualitative data analysis
Selecting one depends on what strengths you are looking for in your research. Some
variables to consider are:
 Research question
 Aims of project
 Timeline