Content Analysis | A Step-by-Step Guide with Examples

Content analysis is a research method used to identify patterns in recorded communication. To conduct content analysis, you systematically collect data from a set of texts, which can be written, oral, or visual:

  • Books, newspapers, and magazines
  • Speeches and interviews
  • Web content and social media posts
  • Photographs and films

Content analysis can be both quantitative (focused on counting and measuring) and qualitative (focused on interpreting and understanding). In both types, you categorise or ‘code’ words, themes, and concepts within the texts and then analyse the results.

What is content analysis used for?

Researchers use content analysis to find out about the purposes, messages, and effects of communication content. They can also make inferences about the producers and audience of the texts they analyse.

Content analysis can be used to quantify the occurrence of certain words, phrases, subjects, or concepts in a set of historical or contemporary texts.

Example: Quantitative content analysis
To research the importance of employment issues in political campaigns, you could analyse campaign speeches for the frequency of terms such as ‘unemployment’, ‘jobs’, and ‘work’ and use statistical analysis to find differences over time or between candidates.

In addition, content analysis can be used to make qualitative inferences by analysing the meaning and semantic relationship of words and concepts.

Example: Qualitative content analysis
To gain a more qualitative understanding of employment issues in political campaigns, you could locate the word ‘unemployment’ in speeches, identify what other words or phrases appear next to it (such as ‘economy’, ‘inequality’, or ‘laziness’), and analyse the meanings of these relationships to better understand the intentions and targets of different campaigns.

Because content analysis can be applied to a broad range of texts, it is used in a variety of fields, including marketing, media studies, anthropology, cognitive science, psychology, and many social science disciplines. It has various possible goals:

  • Finding correlations and patterns in how concepts are communicated
  • Understanding the intentions of an individual, group, or institution
  • Identifying propaganda and bias in communication
  • Revealing differences in communication in different contexts
  • Analysing the consequences of communication content, such as the flow of information or audience responses

Advantages of content analysis

  • Unobtrusive data collection

You can analyse communication and social interaction without the direct involvement of participants, so your presence as a researcher doesn’t influence the results.

  • Transparent and replicable

When done well, content analysis follows a systematic procedure that can easily be replicated by other researchers, yielding results with high reliability.

  • Highly flexible

You can conduct content analysis at any time, in any location, and at low cost. All you need is access to the appropriate sources.

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Disadvantages of content analysis

    • Reductive

    Focusing on words or phrases in isolation can sometimes be overly reductive, disregarding context, nuance, and ambiguous meanings.

    • Subjective

    Content analysis almost always involves some level of subjective interpretation, which can affect the reliability and validity of the results and conclusions.

    • Time intensive

    Manually coding large volumes of text is extremely time-consuming, and it can be difficult to automate effectively.

    How to conduct content analysis

    If you want to use content analysis in your research, you need to start with a clear, direct research question.

    Example: Research question for content analysis
    Is there a difference in how the UK media represents younger politicians compared to older ones in terms of trustworthiness?

    Next, you follow these five steps.

    Step 1: Select the content you will analyse

    Based on your research question, choose the texts that you will analyse. You need to decide:

    • The medium (e.g., newspapers, speeches, or websites) and genre (e.g., opinion pieces, political campaign speeches, or marketing copy)
    • The criteria for inclusion (e.g., newspaper articles that mention a particular event, speeches by a certain politician, or websites selling a specific type of product)
    • The parameters in terms of date range, location, etc.

    If there are only a small number of texts that meet your criteria, you might analyse all of them. If there is a large volume of texts, you can select a sample.

    Example: Selecting the content
    To research media representations of younger and older politicians, you decide to analyse news articles and opinion pieces in print newspapers between 2017 and 2019. Because this is a very large volume of content, you choose three major national newspapers and sample only Monday and Friday editions.

    Step 2: Define the units and categories of analysis

    Next, you need to determine the level at which you will analyse your chosen texts. This means defining:

    • The unit(s) of meaning that will be coded. For example, are you going to record the frequency of individual words and phrases, the characteristics of people who produced or appear in the texts, the presence and positioning of images, or the treatment of themes and concepts?
    • The set of categories that you will use for coding. Categories can be objective characteristics (e.g., aged 30–40, lawyer, parent) or more conceptual (e.g., trustworthy, corrupt, conservative, family-oriented).
    Example: Defining the units and categories of analysis
    Your units of analysis are the politicians who appear in each article and the words and phrases that are used to describe them. Based on your research question, you have to categorise based on age and the concept of trustworthiness. To get more detailed data, you also code for other categories, such as their political party and the marital status of each politician mentioned.

    Step 3: Develop a set of rules for coding

    Coding involves organising the units of meaning into the previously defined categories. Especially with more conceptual categories, it’s important to clearly define the rules for what will and won’t be included to ensure that all texts are coded consistently.

    Coding rules are especially important if multiple researchers are involved, but even if you’re coding all of the text by yourself, recording the rules makes your method more transparent and reliable.

    Example: Developing a set of rules for coding
    In considering the category ‘younger politician’, you decide which titles will be coded with this category (e.g., prime minister, minister, mayor). With ‘trustworthy’, you decide which specific words or phrases related to trustworthiness (e.g., honest and reliable) will be coded in this category.

    Step 4: Code the text according to the rules

    You go through each text and record all relevant data in the appropriate categories. This can be done manually or aided with computer programs, such as QSR NVivo, Atlas.ti, and Diction, which can help speed up the process of counting and categorising words and phrases.

    Example: Coding the text
    Following your coding rules, you examine each newspaper article in your sample. You record the characteristics of each politician mentioned, along with all words and phrases related to trustworthiness that are used to describe them.

    Step 5: Analyse the results and draw conclusions

    Once coding is complete, the collected data is examined to find patterns and draw conclusions in response to your research question. You might use statistical analysis to find correlations or trends, discuss your interpretations of what the results mean, and make inferences about the creators, context, and audience of the texts.

    Example: Analysing the results
    Let’s say the results reveal that words and phrases related to trustworthiness appeared in the same sentence as an older politician more frequently than they did in the same sentence as a younger politician.

    From these results, you conclude that national newspapers present older politicians as more trustworthy than younger politicians, and you infer that this might have an effect on readers’ perceptions of younger people in politics.

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    Amy Luo

    Amy has a master’s degree in History of Art and has been working as a freelance writer and editor since 2014. She is passionate about helping people communicate clearly and effectively.

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