1. AN INTRODUCTION TO CONTENT ANALYSIS
A SALLY
A HELEN
A STAN

2. CONTENT ANALYSIS AS A TECHNIQUE
- for making theory
- by analyzing, examining, and selecting data
- systematically & objectively
CRITERIA OF SELECTION
- clearly & fully expressed rules
- set up before analysis
- explain various data completely
- applied strictly

3. CATEGORIES = MAJOR POINTS = PROS & CONS
SHOULD BE
- connected with what is being discussed
in the messages
- exact wording used in the statement
SHOULD NOT BE
- based on personal opinions
- irrelevant to the messages

4. QUANTITATIVE 量化 vs. QUALITATIVE 質性
- Quantitative : objective, systematic,
procedures of analysis
arbitrary limitation, relevant categories
- Qualitative : definitions, symbols, detailed
explanations, etc
no absolute truth, but context-bound

5. MANIFEST vs. LATENT CONTENT ANALYSIS
- manifest content (surface structure): perceptible, clear, comprehensible message
- latent content (deep structure): implied, unstated message

6. COMMUNICATION COMPONENTS
1. message ↓
2. Sender (participants)
3. Audience (interviews)
- in vivo codes: wording that participants use
in interview
- constructed codes: coded data from in
vivo codes, created by researcher,
academic terms

7. LEVELS & UNITS OF ANALYSIS
words, phrases, sentences, paragraphs,
sections, chapters, books, ideological
stance, subject topic, elements relevant to
the context

8. 1. Simple Random Sampling 簡單隨機抽樣
SAMPLING STRATEGIES
I. Random Sampling
1. Simple Random Sampling 簡單隨機抽樣
to draw subjects from an identified population (母群體)
2. Systematic Sampling 系統抽樣
(Interval Random Sampling 間隔隨機抽樣)
select nth name from the population
Population 母群體總數
Sampling interval = Numbers of persons desired抽樣間隔 取樣數目
* Random Numbers Table 亂數表

9. 3. Stratified Sampling 分層抽樣 - ensure : dissimilarity between stratum ↑
- divide population into stratum
- ensure : dissimilarity between stratum ↑
similarity inside of each strata ↑
∴ produce a representative sample
II. Non-random Sampling
Purposive Sampling 立意抽樣
researcher select subjects according to
his/her research purpose and
understanding of the population
- researcher: with sufficient knowledge or
expertise
- subjects: represent the population

10. GROUNDED THEORY 紮根理論
a process of constructing:
various data →induction/deduction→theory
* explain the phenomena
- development of theory
- collect, analyze, & compare data
systematically
- theory is grounded on data

11. e.g. crime 7 MAJOR ELEMENTS IN WRITTEN MESSAGES
1. Words – the smallest unit, frequently used
2. Themes: simple sentences, string of words with S + predicate (e.g. You are beautiful)
3. Characters: persons
4. Paragraphs: difficult to classify ∵ various things are stated & implied in a single paragraph, infrequently used
5. Items: books, letter, diary, etc
6. Concepts: an idea, more latent
e.g. crime
7. Semantics: how affected the words may be

12. Combinations of Elements
Interview #1 Ah…I do not think I improve grammar and word dictions because my teacher did not correct my grammar and word dictions. Actually, I know I am not good at writing, and I really want to improve my writing ability. Hmm……However, I also wrote articles which were asked from professors as homework while I wrote dialogue journal writing. Well, for the first time, I can accept that I had so many writing mistakes, and I know I still have room to improve it after teacher’s correction. Unfortunately, after many times corrections, the articles which were corrected by professors still appeared many grammar problems and sometimes had word dictions problems. This is why I do not think dialogue journal writing can improve our writing ability. (Shake head)

13. Units and Categories
Units = Codes
‘Code’ the elements into ‘Inductive Categories’
ex. Words, items, themes…

14. Classes and Categories
3 major procedures:
Common classes
2. Special classes
3. Theoretical classes

15. Classes and Categories
Common Classes:
-- a culture in general
People in society to tell apart persons, things, and events
Ex. Age, gender, mother…

16. Classes and Categories
Special Classes:
-- the labels used by members of certain areas
to tell apart persons, things, and events within their limited province
out-group – people in society
in-group – people in the specific group

17. Classes and Categories
Theoretical Classes:
-- emerge in the process of analyzing the data
-- Function:
grounded in the data
Get a theory

19. Open Coding 1. Major Problems: -- can not read between the line
-- do not get the real motivation
2. Can get the points Coding can continue.

20. Open Coding
4 basic guidelines:
Ask the data a specific and consistent set of questions.
What study are these data suitable?
-- What category does this incident indicate?
Benefits:
-- sometimes find unexpected results

21. 2. Analyze the data minutely.
Open Coding
2. Analyze the data minutely.
categories, incidents, interactions, and the like
be coded
<during open coding>
extensive theoretical coverage
<be thoroughly grounded>
systematic coding
★Stop! When it appears repetitious codes!!!

22. Open Coding
3. Frequently interrupt the coding to write a theoretical note.
-- comments ideas <take notes>
4. Never assume the analytic relevance of any traditional variable until the data show it to be relevant.
-- any traditional variable
ex. Age, sex, social class…
-- earn their way into the grounded theory

23. Coding Frames Purposes: 1. To organize the data after open coding
has been completed
2. To identify findings

24. Coding Frames
Axial Coding:
Different ideas organize and construction
2. New ideas

25. MJ 1 MJ 2 MJ 3 Coding Frames Data Open coding Axial Coding MJ 1 MJ 3
*MJ=Major Point

26. A Few More Words on Analytic Induction
Involve several refinements.
Glaser and Strauss suggest:
- Combine 2 data analysis.
1. Analysis of data after coding.
2. Analysis of data while integrating.
Incorporate all appropriate modes of inquiry:
Induction, deduction, and verification

27. Interrogative Hypothesis Testing
4 steps of negative case testing:
1. Make a rough hypothesis.
2. Conduct a thorough search.
3. Discard or reformulate hypothesis.
4. Examine all relevant cases.

28. 4 Safeguards against the potential flaws
Examples should be lifted at random.
Assertion should be more than 3 examples.
Analytic interpretations should be examined by independent reader.
Check no invalidated overall patterns.
Use safeguards can avoids “exampling”

29. STRENGTHS AND WEAKNESSES OF THE CONTENT ANALYSIS PROCESS
Advantages:
It can be virtually unobtrusive.
It is cost effective.
It provides a means of study a process.
Weaknesses:
Limited to examining already recorded messages.
Ineffective for testing causal relationships between variables.
Not appropriate in every research situation.

30. COMPUTERS AND QUALITATIVE ANALYSIS
Using qualitative research programs:
Help qualitative sorting and data management.
Takes times to learn.
Researchers still need to think.
Offer clear directions for novice.
Quantitative research programs help researchers to deal with the vast number of statistical data.