Things You Should Know About Content Analysis: Types, research principles, pros and cons

Content analysis allows researchers in the field of social sciences to analyse the meanings and relationships of words or other concepts and can be conducted quantitatively or qualitatively. It follows a structured approach and helps to categorise content according to the research question. Researchers can, for example, evaluate language used within a news article to search for (gender) bias or inappropriate comments.

Basically, all types of texts (including audio-visual material), such as interviews (open-ended questions), field research notes, conversations, advertisements, books, discussions, speeches, newspaper headlines, media or historical documents are suitable data for your content analysis. However, in order to conduct a thorough analysis, the respective text(s) must be properly prepared, i.e. coded or broken down into manageable categories for analysis. Once the text is divided into categories, the codes can then be further categorised into “code categories”, depending, of course, on the individual research goal.

Analysis Types 

There are two types of content analysis – a quantitative and a qualitative one. Depending on the approach used in the analysis and your research question(s), the results obtained may entail different findings, conclusions and/ or interpretations.

Quantitative Content Analysis

In a quantitative content analysis technique, various types of content are systematically coded and analysed, usually through quantifying the occurrence and frequency of certain words as well as explicit or implicit concepts in the respective text. This can include social media and media analysis, sentiment analysis and big data approaches. Quantitative content analysis is used for written, visual or oral content.

Qualitative Content Analysis

A qualitative content analysis, on the other hand, comprises a subjective interpretation of the content. It entails more than a mere counting process of text passages. Instead, it identifies and analyses meaning and relationships within textual data in a replicable and systematic manner. Such a qualitative approach is mostly used to analyse interviews. Categories are used to analyse meaning, similarities and differences across a set of interviews.  

Key Research Principles to Have in Mind When Analysing Content

When conducting a content analysis, it is of utmost importance to consider the following key research principles:

Reliability: The reliability of data is an important principle when analysing content. Coding errors can never be eliminated, but only reduced to a minimum. Since researchers are only human, errors are absolutely legit. Generally, 80% is an acceptable margin for reliability. When defining the principle of reliability, it is important to keep in mind the stability, i.e. consistently re-code the same data in the same way over a period of time, reproducibility, i.e. always classify categories in the same way and accuracy of data, i.e. the extent to which the classification statistically corresponds to a certain norm.

Validity: The second key principle in content analysis is the validity of data. Validity is firstly achieved through a certain closeness of the defined categories. Further, the conclusions we reach turn our content analysis in a valid research approach. Some of the following questions have to be considered when drawing our conclusions: What level of implication is allowable? Do the conclusions correctly follow the data? Are the results obtained explainable by other phenomena? Last but not least, the generalisability of the results to a certain theory does also play a crucial role when defining the validity of content analysis. 

Advantages and Disadvantages of Content Analysis

Below, we provide a quick overview of the key advantages and disadvantages of content analysis:

Pros

Content analysis…

… can be used to systematically examine communication patterns.

… is non-invasive (in contrast to simulating social experiences or collecting survey answers).

… allows both qualitative and quantitative approaches.

… is a cost-effective research method that can be conducted inductively or deductively (depending on the research purpose). 

… follows a clear and well-defined structure (which makes it easy to understand for “beginners”).

… is used and accepted widely across different fields, e.g. education, health science, political and cultural studies, history, leadership studies, and marketing. 

… can be statistically analysed (computer-assisted analysis can additionally simplify the analysis process).

Cons

Content analysis…

… is time-consuming.

… is subject to increased error (particularly when applying a rather interpretative approach).

… may not fit the complexity of certain texts.

… may not efficiently deal with the (social) context of a text (you might want to take a look at discourse analysis if this is the case).

… can sometimes be difficult to computerise.

… is more significant when combined with other research methods such as interviews.