This document provides an overview of content analysis as a research technique. It defines content analysis as objective, systematic analysis and categorization of communication content. The workshop covers the procedures of content analysis, including design, unitizing, sampling, coding, drawing inferences and validation. Examples of using content analysis to analyze text data from interviews are presented, showing coding categories, frequency calculations and correlations. Content analysis is described as a useful technique for making inferences from qualitative data in an objective and replicable manner.

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Workshop
Teknik Analisis Data dengan
Menggunakan ‘Content Analysis’
Pemateri: Dr.phil. Maria Teodora Ping, M.Sc.
Fakultas Keguruan dan Ilmu Pendidikan
Universitas Mulawarman
Structure of the Workshop
O Introduction to ‘Content Analysis’
O Procedures of ‘Content Analysis’
O Examples of Data Analysis
O Practices
Introduction to Content
Analysis
O Definitions and Basic Concepts
‘Method’
‘Approach’
‘Technique’
Introduction cont.
Selected definitions of ‘Content Analysis’
Berelson (1952): ‘a research technique for the objective,
systematic, and quantitative description of the manifest
content of communication’
Holsti (1969): ‘any technique for making inferences by
objectively
and systematically identifying specified characteristics of
messages.’
Krippendorf (1989): ‘a research technique for making a
replicable and valid inferences from data to their context’
Introduction cont.
“an approach of empirical, methodological controlled
analysis of texts within their context of communication,
following content analytic rules and step by step models,
without rash quantification” (Mayring, 2000)
“any qualitative data reduction and sense-making effort
that takes a volume of qualitative material and attempts to
identify core consistencies and meanings” (Patton, 2002)
“a research method for the subjective interpretation of the
content of text data through the systematic classification
process of coding and identifying themes or patterns”
(Hsieh & Shannon, 2005)
Introduction cont.
White and Marsh (2006): ‘a highly flexible research
method that has been widely used in library and
information science (LIS) studies with varying
research goals and objectives … a systematic,
rigorous approach to analyzing documents
obtained or generated in the course of research’
Fraenkel, Wallen and Hyun (2012): a technique
that enables researchers to study human behavior
in an indirect way, through an analysis of their
communications

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Introduction cont.
Application of Content Analysis
O Content analysis has wide applicability in educational
research.
O Content analysis can give researchers insights into
problems that they can test by more direct methods.
O There are several reasons to do a content analysis: to
obtain descriptive information of one kind or another;
to analyze observational and interview data; to test
hypotheses; to check other research findings; and/or
to obtain information useful in dealing with
educational problems.
Introduction cont.
Categories and Categorisation in Content
Analysis
O Predetermined categories are sometimes
used to code data (deductive)
O Coding can also be done by using categories
that emerge as data is reviewed (inductive)
O ‘Open Matrix’ coding
Introduction cont.
Advantages of Content Analysis
Content analysis can:
O quantify largely qualitative information
O facilitate unobtrusive measurement
O cope with large volumes of source material
O add qualitative richness to otherwise
quantitative data
O validate evidence from other sources
Introduction cont.
Disadvantages of Content Analysis
O costly and time-consuming
O pose reliability and validity problems
O challenged as too subjective
Procedures
O Design
O Unitizing
O Sampling
O Coding
O Drawing Inferences
O Validation
(Krippendorf, 1989)
Procedures cont.

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Procedures cont.
O Inductive Content Analysis Procedure (Mayring, 2000)
Procedures cont.
O Deductive Content Analysis Procedures (Mayring, 2000)
Procedures cont.
Steps involved in Content Analysis (Fraenkel,
Wallen and Hyun, 2012)
O Determining Objectives
O Defining Terms
O Specifying the Unit of Analysis
O Locating Relevant Data
O Developing a Rationale
O Developing a Sampling Plan
O Formulating Coding Categories
Procedures cont.
Coding Categories
O Developing emergent coding categories requires a high
level of familiarity with the content of a communication.
O In doing a content analysis, a researcher can code
either the manifest or the latent content of a
communication, and sometimes both.
O The manifest content of a communication refers to the
specific, clear, surface contents: the words, pictures,
images, and such that are easily categorized.
O The latent content of a document refers to the meaning
underlying what is contained in a communication.
Procedures cont.
Validity and Reliability
O Reliability in content analysis is commonly
checked by comparing the results of two
independent scorers (categorizers);
intercoder reliability calculation
O Validity can be checked by comparing data
obtained from manifest content to that
obtained from latent content.
Procedures cont.
Data Analysis and Interpretation
O A common way to interpret content analysis data
is by using frequencies (i.e., the number of
specific incidents found in the data) and
proportion of particular occurrences to total
occurrences.
O Using the coding to develop themes to facilitate
synthesis.
O Computer analysis is extremely useful in coding
data once categories have been determined.

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Procedures cont.
Descriptive Statistics
O Frequency Calculation
O Cross-tabulation
O Chi- Square
O Cramer’s V Correlation
Examples of Data Analysis
O Example of a Code Book
O Using Software (QDAMiner)
Examples of Data Analysis
cont.
Examples of Data Analysis
cont.
140
120
100
80
60
40
20
0
R-F: Naming
R-F:PicDesc
R-F: Conf
R-F: Corr
R-F: Elab
R-F: PersC
R-F: PersRe
R-F: Recall
R-F: TextPr
R-F: TextRC
R-F: GenKnw
R-F: Eval
S-I: Naming
S-I: PicDesc
S-I: PersC
S-I: TextRC
S-I: GenKnw
S-I: AskQues
S-I: InitIntrc
S-I: TextPr
TEK DS 1
TEK DS 2
TEK M
TEK RS
TEK SH
Examples of Data Analysis
cont.
Examples of Data Analysis
cont.
Participants * EduStrategies Crosstabulation
Count
EduStrategies
Personal
Comments
and
Book Focus Confirmation Elaboration Opinions
Total
Personal
Responses
Management
Style
Participants 1 8 88 47 12 6 42 203
2 1 32 7 3 6 10 59
3 1 61 14 3 19 57 155
4 1 3 1 6 1 5 17
5 1 45 11 4 10 54 125
Total 12 229 80 28 42 168 559

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Examples of Data Analysis
cont.
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 95,588a 20 ,000
Likelihood Ratio 79,623 20 ,000
Linear-by-Linear Association 27,573 1 ,000
N of Valid Cases 559
Examples of Data Analysis
Symmetric Measures
Value Asymp. Std. Errora Approx. Tb Approx. Sig.
Nominal by
Nominal
Phi ,281 ,000
Cramer's V ,281 ,000
Interval by Interval Pearson's R -,243 ,048 -4,625 ,000c
Ordinal by Ordinal Spearman
Correlation
-,280 ,050 -5,389 ,000c
N of Valid Cases 343
Contact?
O mariateodoraping@fkip.unmul.ac.id
O maria.t.ping@gmail.com
Examples of Data Analysis
cont.
Qualitative Analysis- Theoretical Triangulation
Example 7 : Text- Reader Connect (Code/ Category)
E : ganz viele Teddys, ne? Verschiedene Teddys.
A lot of teddy (bears), right? Different sorts of teddy (bears).
K4 : Ich hab IIIccchhh hhhaaabbb aaaauuuucccchhhh vvvviiiieeeelllleeee TTTTeeeeddddddddyyyyssss
I also have a lot of teddy bears
(Excerpt 124, Transcript 2 Case 2)
The child in the example 7 above responded to the educator’s utterance by
relating the object in the picture being discussed to her personal life or
experience. As discussed earlier in the section concerning children’s responses
in Case 1, some studies such as the ones conducted by Cochran- Smith (1986)
and Moschovaki & Meadows (2005), which assessed adult- child shared book
reading activities reported that children indeed produced responses which
connected the story or the text with their own lives.
(Ping, 2012)
References
O Berelson, B. (1952). Content analysis in communication research. New York: Free
Press. A pioneering text on content analysis
O Fraenkel, Jack R., Wallen, Norman E. and Hyun, Hellen H. (2012) How to Design
and Evaluate Research in Education 8th Edition. McGraw Hill
O Holsti, P. R. (1969). Content analysis for the social sciences and humanities.
Reading, MA: Addison-Wesley. An introductory text on content analysis.
O Hsieh, H.-F., & Shannon, S.E. (2005). Three approaches to qualitative content
analysis.Qualitative Health Research, 15(9), 1277-1288.
O Krippendorff, K. (1989). Content analysis. In E. Barnouw, G. Gerbner, W. Schramm,
T. L. Worth, & L. Gross (Eds.), International encyclopedia of communication (Vol. 1,
pp. 403-407). New York, NY: Oxford University Press. Retrieved from
http://repository.upenn.edu/asc_papers/226
References cont.
O Mayring, P. (2000). Qualitative content analysis. Forum Qualitative
Social Research/Forum Qualitative Sozialforschung, 1(2). Retrieved
September 24, 2005, from http://www.qualitativeresearch.net/fqs-texte/
2-00/2-00mayring-e.htm.
O Patton, M.Q. (2002). Qualitative Research and Evaluation Methods.
Thousand Oaks, CA: Sage.
O Ping, Maria Teodora. (2012). Dialogic Oriented Shared Book Reading
Practices for Immigrant Children in German Kindergartens. Florida:
Universal- Publishers.com
O White, M.D. and Marsh, E.E. (2006). Content Analysis: A Flexible
Methodology. LIBRARY TRENDS, Vol. 55, No. 1, Summer 2006
(“Research Methods,” edited by Lynda M. Baker), pp. 22–45 © 2006
The Board of Trustees, University of Illinois