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

CONTENT ANALYSIS MLIS-10 Information Analysis, Consolidation,

Repackaging & Retrieval Unit-2 Consolidation & Repackaging

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 termContent 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

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.

Types of Content Analysis

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-talkWant to study argument in decision-making discussionMight 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 questionFrequenciesDifferences 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