Content analysis is a guide consisting of coded documents of transcripts, newspapers, speech, and films that is used in order to study the counts of word-phrase clusters for the purpose of conducting statistical analysis. Usually, researchers in media and communications perform cluster analysis by creating a dictionary of word-phrase clusters in the form of classified conceptual categories for the purpose of counting those conceptually categorized words and phrases. Content analysis mainly focuses on those applications that are based on print media, media transcripts, and so on. In other words, content analysis mainly focuses on communication-related applications.
Researchers may conduct content analysis for any of the following reasons:
- Content analysis is carried out in order to understand the change in the trend of the content over time.
- Content analysis can be used to explain why there is special attention or focus on certain topics of content. For example, the glamorous field consisting of celebrity gossip is a topic that is a huge focus of attention for people of all ages.
- Content analysis can be used to compare the international differences in the content.
- Content analysis helps in comparing the group differences in the content.
- Content analysis helps in tracing the theoretical development in intellectual history.
- With the help of content analysis, the researcher can draw a comparison between the actual content and the intended content.
- With the help of content analysis, the researcher can detect and then expose the use of biased terms in the research involving information that influences the opinions or behaviors of people.
- With the help of content analysis, the researcher can test hypotheses about the cultural and symbolic use of terms.
- Content analysis can be used by a researcher for coding purposes. With the help of content analysis, researchers can code open ended survey questions. (The open ended survey questions are the ones that do not have any definite answers.)
There are certain terms used in content analysis that can be helpful for understanding content analysis.
- A term called unitizing in content analysis is a process by which the researcher establishes a unit of the analysis. For example, the researcher in content analysis may unitize the words, sentences, or paragraphs.
- Sampling is one of the important tools in content analysis. Generally, the content is too vast in content analysis. It is usually not possible for the researcher to study the content of all units in content analysis. So the researcher utilizes the technique of sampling in order to make his content analysis less complicated. Sampling in content analysis usually involves the counting under some construct, which involves the development of different kinds of synonymous terms.
- The data in content analysis must be free from complexity. This means that the researcher should make the content into a reduced format that is less complicated. This is basically done in content analysis by employing certain summary statistical measures. Thus, in content analysis, coding is done to make the content comparatively less complicated.
- The inference is a major part of content analysis. A contextual phenomenon in content analysis must be analyzed in order to obtain a valid inference of the context for findings.
Content analysis involves conclusions that are usually communicated by the researcher in a narrative manner.
There are basically two assumptions in content analysis:
- Content analysis is generally assumed to be subjected to the problems of sampling.
- Content analysis is assumed to be based upon the context for words and meanings.
There are certain software resources for conducting content analysis:
- ATLAS.ti is used in content analysis as software for text analysis and model building.
- The General Inquirer is the classic package for content analysis.
- Intext and TextQuest are software developed by Harald Klein for content analysis.
