Dr. N K Swain’s 
research prescription for LIS novices
CONTENT ANALYSIS 
MLIS-10 Information Processing & Retrieval 
Unit-2 Information Systems & Products 
Academic Session 2014-15
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
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.
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.
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.
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
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
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.
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.
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
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.
Coding … 
 Coding scheme generates from a theory or 
past research findings 
 Use theory and research to develop a set of 
relevant categories
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
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
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
Statistical Analysis 
Codes are entered in statistical package 
(SPSSX, SAS, Excel, etc) 
Statistics depend on research question 
Frequencies 
Differences in categories (chi-square)
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.
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.
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.
Look into Dr N K Swain’s slides 
THANK YOU

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

  • 1.
    Dr. N KSwain’s research prescription for LIS novices
  • 2.
    CONTENT ANALYSIS MLIS-10Information Processing & Retrieval Unit-2 Information Systems & Products Academic Session 2014-15
  • 3.
    Dr. Nirmal KumarSwain 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 Analysisis 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 analysiswas 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  thecodes 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 beanalyzed Words, phrases, sentences, paragraphs, sections, chapters, books, ideological stance, subject topic, even sound and video recordings, elements relevant to the context
  • 9.
    Types of ContentAnalysis 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 • Looksdirectly 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 Needto 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 Wantto 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 Codesare 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 • Canbe 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 DrN K Swain’s slides THANK YOU