Content Analysis explained plus example

Content Analysis: this article provides a practical explanation of the term content analysis in the context of research skills. The article begins with a general definition and explanation, followed by a step-by-step plan for performing this type of analysis, including an example at each step. You will also find an overview of the benefits and drawbacks of applying such an analysis in a study. Enjoy reading!

What is a content analysis? A brief explanation

Content analysis is a research method that can identify patterns in recorded communications.

By systematically collecting data from different types of texts, such as written documents, speeches, web content or visual media, researchers can then discover valuable information about the goals, messages and effects of communication.

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In this type of analysis, words, themes and concepts in the texts are categorized or “coded”, allowing for both quantitative and qualitative analyses.

Quantitative analysis focuses on counting and precisely measuring events, while qualitative analysis aims to interpret and understand the meaning and semantic relationships of words and concepts.

A Content Analysis example

An example. In a political campaign, content analysis can help researchers understand the importance of employment issues.

By analyzing political leaders’ campaign speeches, they can quantify the frequency of terms such as unemployment, jobs and employment and analyze them statistically for differences over time or between candidates.

In addition, they can also take a qualitative approach, examining the word unemployment in speeches, identifying related words or phrases and analyzing the meanings of these relationships. The aim is then to gain a deeper understanding of the intentions and target groups of different campaigns.

In which fields are content analyzes used?

Content analytics is applied in a variety of fields, including marketing, media studies, anthropology, cognitive science, psychology, and social sciences.

The goals of this type of analysis range from identifying correlations and patterns in communication to understanding intentions and analyzing the consequences of communication.

Step-by-step plan for performing a content analysis

Below you will find the steps that are followed when performing a content analysis.

Please note that the approach to the analysis may differ per situation. The steps you read about below are general steps.

Step 1: Select the content you want to analyze

Start by choosing specific texts or material to examine in the content analysis. This may include sources such as news articles, social media posts, interviews or documents.

Example: Select a collection of 100 newspaper articles from reputable sources that deal with climate change.

Step 2: Define the units and categories of analysis

Determine the specific units within the content you want to analyze and create categories to classify them. Units can be individual words, sentences, paragraphs, or even entire sections.

Example: Define a unit as a single sentence in the newspaper articles and create categories such as “causes of climate change”, “impacts on the environment” and “policy recommendations”.

Step 3: Develop a set of coding rules

Create a clear and consistent set of guidelines for assigning codes to the units based on the established categories. These rules ensure consistent and reliable coding during analysis.

Example: Code a sentence discussing the role of greenhouse gasses as “GG” and a sentence pointing to renewable energy solutions as “RES”.

Step 4: Code the text according to the rules

Systematically apply the coding rules to the content and assign the correct codes to each unit.

Please read and interpret the content carefully to determine the most accurate code based on established guidelines.

Example: Read each sentence in the newspaper articles and assign the relevant code (GG or RES) to indicate whether the sentence discusses greenhouse gases or renewable energy solutions.

Step 5: Analyze the results from the Content Analysis and draw conclusions

Once coding is complete, analyze the encoded data to identify patterns, frequencies, and relationships between categories.

Calculate percentages or frequencies to quantify the occurrences of specific codes. Interpret the results to draw meaningful conclusions about the content.

Example: Calculate the percentage of sentences related to “causes of climate change” versus “policy recommendations” to understand the focus of the articles.

Analyze how often the code GG occurs compared to the code RES to assess the emphasis on renewable energy solutions.

Sampling as a part of the content analysis

Sampling is an important aspect of content analysis. Sampling determines which texts are included in the analysis.

There are several sampling methods that researchers can use:

Random sampling

In this method, texts are randomly selected from the population. Random sampling ensures that the selected texts are representative of the larger population.

It reduces the risk of bias and allows generalization of the findings to a broader context.

Example: In a content analysis of customer reviews on an e-commerce platform, random sampling can be used to obtain a random selection of reviews from the full pool of available reviews.

Purposive sampling

In purposive sampling, texts are selected based on specific criteria or characteristics relevant to the research purposes.

Researchers deliberately select texts that offer valuable insights or illustrate certain themes or perspectives.

Example: In an analysis of political speeches, purposive sampling can be used to select speeches by major political figures or to choose speeches that address specific policy issues relevant to the study.

Sampling units

Sampling units refer to the elements within the selected texts that will be analyzed. Researchers must determine the appropriate size and scope of analysis by defining the sampling units.

These units can vary depending on the research question, such as individual words, sentences, paragraphs or entire documents.

Example: In a content analysis of online news articles, the sampling units might be individual paragraphs within the articles. Researchers may choose to analyze the statements in these paragraphs.

Benefits of content analysis in research

The benefits are:

Objectivity

Content analysis uses a systematic and structured approach, making it possible to obtain objective and reproducible results. It provides a quantitative basis for analysis and interpretation.

Large amount of data

Content analysis enables researchers to efficiently analyze large amounts of texts.
This allows them to spot patterns and trends that would otherwise be difficult to identify.

Flexibility

Content analysis can be applied to different types of texts, such as written, oral or visual sources. This makes it a versatile method that can be adapted to various research questions and disciplines.

Wide applicability

Content analysis is used in various fields such as marketing, media research, sociology, psychology and more. It offers a valuable tool for gaining insight into communication processes and their effects.

Drawbacks of content analysis in research

The use of content analysis also has some drawbacks. Read them below.

Limited to selected content

These types of analysis relies on the availability of recorded communications, such as written documents, interviews, social media posts, etc. It may limit interpretation to what is actually captured and may miss important contextual information.

Subjectivity of the Content Analysis

Because content analysis requires the interpretation of the researcher in coding and analyzing the data, there can be a degree of subjectivity. The researcher’s personal biases or interpretations may affect the results.

Time intensive

These types of analysis can be a time-consuming method, especially when analyzing large amounts of texts. It requires patience and accuracy in coding and analyzing the data.

Possible coding issues

Creating coding rules can present challenges. Differences in interpretation can arise between different codes, which can affect the reliability and consistency of the analysis.

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Now it’s your turn

What do you think? Do you recognize the explanation about content analysis? Have you ever used content analysis for research? What challenges did you face while performing this analysis? How important do you think it is to have a representative sample when conducting a content analysis? What other things do you think researchers can use to ensure the reliability of the content analysis? Do you have tips or comments?

Share your experience and knowledge in the comments box below.

More information

Stemler, S. (2000). An overview of content analysis. Practical assessment, research, and evaluation, 7(1), 17.
Drisko, J. W., & Maschi, T. (2016). Content analysis. Pocket Guide to Social Work .
Weber, R. P. (1990). Basic content analysis (Vol. 49). Sage.
Krippendorff, K. (2018). Content analysis: An introduction to its methodology. Sage publications.

How to cite this article:
Janse, B. (2023). Content Analysis. Retrieved [insert date] from Toolshero: https://www.toolshero.com/research/content-analysis/

Original publication date: 11/14/2023 | Last update: 11/14/2023

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