This is about content analysis both for the students of library and information science as well s for tutors.

1. Dr. N K Swain’s
research prescription for LIS novices

2. CONTENT ANALYSIS
MLIS-10 Information Processing & Retrieval
Unit-2 Information Systems & Products
Academic Session 2014-15

3. Dr. Nirmal Kumar Swain
Associate professor
Department of Library and Information Science
Vivekananda Library Building
Maharshi Dayananda University
Rohtak – 124002, Haryana, India
Home: www.nirmalkumarswain.com
E-Mail: drnkswain@gmail.com

4. Introduction
Content Analysis is a technique / approach
started with the mass communication
professionals (it is said) but eventually
people from the disciplines of Anthropology,
Sociology, Business Research, Political
Science and more prominently Library &
Information Science utilize the benefits of
this content analysis as an approach or
method in their disciplinary activities.

5. History
Content analysis was initially limited to studies which
examined texts for the frequency of the occurrence of
identified terms in a content. Explored in 1040s got
momentum in 1950s and 1960s “Focusing on
concepts rather than simply words, and on semantic
relationships rather than just presence (de Sola Pool
1959). This is now utilized to explore mental models,
with linguistic, affective, cognitive, social-cultural,
communitarian and historical significance.

6. Defining the term
Content analysis is a research technique (or method of
inquiry) for systematic and replicable analysis of the
content of communication, and for making
inferences from that data to their context.
According to Berelson “Content analysis is a research
technique for the objective, systematic and
quantitative description of the manifest content of
communication”
Content analysis is a method of coding qualitative
and/or quantitative narrative data to identify the
prevalence of key themes and issues in relation to a
particular context.

7. Usefulness
 the codes for analysing your data can be
derived before the data is collected
• it is important to identify the context within
which certain words and terms are used
• the results do not need to be generalisable to
the wider population

8. Content to be analyzed
Words, phrases, sentences, paragraphs,
sections, chapters, books, ideological stance,
subject topic, even sound and video
recordings, elements relevant to the context

9. Types of Content Analysis
1. Conceptual Analysis
A concept is chosen for examination, and the analysis
involves quantifying and tallying its presence. The focus
here is on looking at the occurrence of selected terms
within a text.
2. Relational Analysis :
It begins with the act of identifying concepts present in a given
text or set to texts and seeks to go beyond presence by
exploring the relations between the concepts identified.

10. Preparation of data
It is easier wit h written data however if
data is “spoken,” (interviews, focus groups,
videotaped groups, etc), it is best to have
the data transcribed. Can make code from
spoken text, but much more difficult.

11. Elements in content
 Words - the smallest unit, frequently used
 Themes - simple sentences, string of words with
subject + predicate (e.g. you look beautiful)
 Characters: different person with attitude
 Paragraphs: difficult to classify ∵ various things are
stated & implied in a single paragraph, infrequently
used
 Items: books, research results, letter, diary, etc
 Concepts: an idea, more latent e.g., plagiarism
 Semantics: how affected the words may be

12. Advantages
• Looks directly at communication via texts or
transcripts, and hence gets at the central aspect of
social interaction.
• Can allow for both quantitative and qualitative
operations.
• Can provide valuable historical/cultural insights
over time through analysis of texts.
• Allows closeness to text which can alternate
between specific categories and relationships and
also statistically analyzes the coded form of the
text.

13. Coding …
 Coding scheme generates from a theory or
past research findings
 Use theory and research to develop a set of
relevant categories

14. Developing Coding Scheme
 Begin developing categories based on
theory and research findings
 Test category scheme against data that is
similar to, but not included in, final data set
 Revise coding scheme based on testing
 Process is best done by two or more
people to discuss similarities and
differences
 Continue process until coding scheme is
both exhaustive and exclusive

15. Coding Units
Need to determine your “unit of analysis”
WHAT will you define as your coding units?
 You want sensible, but rich, units
Units need to fit research question, object of
research interest, coding
 Words
 Thought units (subject-verb; complete thought)
 Sentences, Paragraphs, Simple turn, Complete
turns-at-talk, Partnered turns-at-talk,
 Whole discussions
 Your choice of “unit” is based on your research
question, your coding scheme, what you know
about your data

16. Example Units
Want to understand emotion in student
discussions Might choose turn-at-talk
Want to study argument in decision-making
discussion
Might choose thought-unit (because more
than one argument can occur in larger
units)
 Want to study conflict in online
discussion
 Might choose whole discussion, or
partnered turns-at-talk

17. Statistical Analysis
Codes are entered in statistical package
(SPSSX, SAS, Excel, etc)
Statistics depend on research question
Frequencies
Differences in categories (chi-square)

18. Advantages …
• Looks directly at communication via texts or
transcripts, and hence gets at the central aspect of
social interaction.
• Can allow for both quantitative and qualitative
operations.
• Can provide valuable historical/cultural insights over
time through analysis of texts.
• Allows closeness to text which can alternate between
specific categories and relationships and also
statistically analyzes the coded form of the text.

19. Cont …
• can be used to interpret texts for purposes such
as the development of expert systems.
• is an unobtrusive means of analyzing
interactions.
• provides insight into complex models of
human thought and language use.
• when done well, is considered as a relatively
"exact" research method.

20. Disadvantages
• Can be extremely time consuming.
• Is subject to increased error, particularly when
relational analysis is used to attain a higher level
of interpretation.
• Is inherently reductive, particularly when dealing
with complex texts.
• Tends too often to simply consist of word counts.
• Can be difficult to automate or computerize.
• Often disregards the context that produced the
text, as well as the state of things after the text is
produced.

21. Look into Dr N K Swain’s slides
THANK YOU