Transcript Qualitative Data Analysis

More on Qualitative
Data Collection and
Data Analysis
Forms of Data
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John Creswell (1998) notes there are four
basic types of data that may be collected,
depending on the methodology used:
 Observations
 Interviews
 Documents
 Audio-visual
materials
Main Types of Qualitative Notes
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Field Notes (to record all your observations)
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running account of what happens or transcriptions/observations of videos
 important to be thorough in taking field notes, particularly at the earliest
phases of research
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Personal Notes (Personal Diary)
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personal reactions, how you feel, self-reflection, memories, and
impressions
 like a diary, so you can later see your own influence on the data and the
effects of personal events on the data collection
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Methodology Notes
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Description of methods used, reasons for using those methods, ideas for
possible changes
 used for keeping track of changes and rationale for changes
 can include methods of analysis.
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Theoretical Notes (Analytic Memo)
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emergent trends, hypotheses
can include guesses and hunches to follow up later in your research.
also tp describe changes made to emergent categories and hypotheses,
and the reasons why those changes were made
What is content analysis?

Berg (2009) calls it a “careful, detailed,
systematic examination” of the data
gathered through your observations or
interviews, or sources like documents,
archives, diaries, etc.
Approaches to the Analysis
 Interpretative Approaches
Treat
social action and human activity as text
 Social Anthropological Approaches
Analysis
of field notes and other data
 Collaborative
Work
Social Research Approaches
with stakeholders
Content Analysis
 Systematic
and objective
 Manifest Content
physically
present and countable
elements (what is actually seen)
 Latent
Content
interpretive
reading of underlying
meaning and semantics (semiotic)
Communication Components
–– message –– audience
 Who is the sender?
 What is the message? – theme, emphasis, intent
 What group is the message directed at?
 In Vivo Codes
 literal terms used by individuals under
investigation
 represents behavioral process
 Sociological Constructs
 Concepts formulated by the analyst
 Sender
What to examine
 What
is the level and unit of analysis?
Manifest
Content
 Words
 Characters
 Images
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Items
Latent
Content
 Themes
Concepts
 Semantics

Classes and Categories
 Categories
can be deductive (drawn from
theory) or inductive (drawn from data) or
combination of the two
 Distinguishing between and among
persons, things, and events
 Common
classes—used by virtually everyone
 Special Classes—used by members of certain
areas (argot or jargon)
 Theoretical Classes—provides an overarching
pattern (concepts)
Interrogative Hypothesis Testing
 Make
a rough hypothesis
 Search
for negative cases
 Examine
all relevant cases
Method of Constant Comparison
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Look for indicators of categories in events and
behavior - name them and code them on
document(s)
Compare codes to find consistencies and differences
Consistencies between codes (similar meanings or
pointing to a basic idea) reveals categories. So need
to categorize specific events
Create memos on the comparisons and emerging
categories
Eventually category saturates when no new codes
related to it are formed
Certain categories become more central focus - axial
categories and perhaps even core category.
Analytic Induction
Look at an event or activity and develop a
hypothetical statement of what is going on.
 Look at an similar instance and see how it
fits the hypothesis. Revise hypothesis.
 Look for exceptions to hypothesis. Revise
hypothesis to fit all examples encountered.
 Eventually will develop a hypotheses that
accounts for all observed cases.
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Other Analytic Strategies
Narrative approach: detailed narrative of
field experience (descriptive)
 Ideal types: (Weber) compare ideal forms
(i.e. suggested by theory) to empirical
observations
 Successive Approximation: move back
and forth between theory and data until
theory (or generalization) is perfected
 Illustrative Method: find empirical
examples in the data to support the theory
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The Framework Approach
(source: Pope et al. 2000 Analysing Qualitative Data)
Stage 1

· Familiarisation—immersion in the raw
data (or typically a pragmatic selection
from the data) by listening to tapes,
reading transcripts, studying notes and so
on, in order to list key ideas and recurrent
themes
Framework Stage 2
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· Identifying a thematic framework—identifying
all the key issues, concepts, and themes by
which the data can be examined and
referenced. This is carried out by drawing on a
priori issues and questions derived from the
aims and objectives of the study as well as
issues raised/observed within the data and/or
views or experiences that recur in the data. The
end product of this stage is a detailed index of
the data, which labels the data into manageable
chunks for subsequent retrieval and exploration
Framework Stage 3
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· Indexing—applying the thematic
framework or index systematically to all
the data in textual form by annotating the
transcripts with numerical codes from the
index, usually supported by short text
descriptors to elaborate the index heading.
Single passages of text can often
encompass a large number of different
themes, each of which has to be recorded,
usually in the margin of the transcript
Framework Stage 4
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· Charting—rearranging the data according to the
appropriate part of the thematic framework to
which they relate, and forming charts. For
example, there is likely to be a chart for each key
subject area or theme with entries for several
respondents. Unlike simple cut and paste
methods that group verbatim text, the charts
contain distilled summaries of the text. The
charting process involves a considerable amount
of abstraction and synthesis.
Framework Stage 5
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· Mapping and interpretation—using the
charts to define concepts, map the range
and nature of phenomena, create typologies
and find associations between themes with a
view to providing explanations for the
findings. The process of mapping and
interpretation is influenced by the original
research objectives as well as by the themes
that have emerged from the data
themselves.
Content Analysis
 Strengths
 Virtually
unobtrusive
 Cost effective
 Trend identification
over time
 Weaknesses
 Limited
to
examining already
recorded
messages
 Ineffective for
testing causal
relationships