INSPIRING CREATIVE AND INNOVATIVE MINDS CONTENT ANALYSIS A careful, detailed, systematic examination and interpretation of a particular body of material in an effort to identify patters, themes, biases and meanings (Berg & Latin, 2008)

-Should be related to the literature and broader concerns and to the original research questions -The analysis provides the researcher a means by which the subjects or the authors view their social worlds and how it fit into the larger frame -“It is a passport to listening to the words of the text and understanding better the perspectives of the producer” (Berg, 2008)

Manifest Versus Latent Content Analysis -Manifest content – elements that are physically present and countable -Latent content – deep structural meaning conveyed by the message

Category Development -Inductive – the researcher “immerse” in the documents in order to identify the dimensions or themes -Deductive – the researcher use some categorical scheme suggested by a theoretical perspective

What to count -Words – frequency distribution of specified words or terms -Themes – a string of words (simple sentence) -Characters – the number of times a specific person or persons mentioned -Paragraphs – combination of various and often numerous thoughts

-Items – the whole unit of the sender’s message (letter, speech, etc.) -Concepts – conceptual clusters (ideas), e.g., concept of deviance (toward more latent than manifest content) -Semantics – how strong a word to the overall sentiment of the sentence

Combinations of Elements -In certain situation content analysis requires the use of combinations of the content analytic elements -Eg., in understanding certain concepts, the researcher might wants to use a combination of item and paragraph, and so on

Open Coding -The researcher need to hold their interpretations, questions, or even possible answers in order to allow the coding process is completed -Strauss (1987) – “believe everything and believe nothing”

Strauss (1987) suggested 4 guidelines in conducting open coding: 1. Ask the data a specific and consistent set of questions 2. Analyse the data minutely 3. Frequently interrupt the coding to write a theoretical note 4. Never assume the analytic relevance of any traditional variable (gender, age, and so on) until the data show it to be relevant

Asking Specific and Consistent Questions -The researcher must keep the general question in mind -The original of the study may not be accomplished but rather an alternative or unanticipated goal may be identified in the data

Analyse the Data Minutely -The researcher is required to analyse the data minutely -The researcher should consider how detail the data can be coded to ensure every part and information of the data is analysed -The process will eventually saturate the document

Frequently Interrupt the Coding -A comment in the document triggers ideas – jot down -Fail to do so, the idea is very much likely to be forgotten

Never Assume Any Traditional Variable -The variables should be grounded in the data -The researcher should look into the data whether the variables are relevant to the assumption of the study or not

Negative Case Testing -The researcher intentionally seeking negative or unique cases until the data are saturated and built into an emerging pattern -Null hypothesis trick (Becker, 1998) – the assumption the researcher have on the data to reveal no patterns of relationships

Thank you very much for your attention…