Content analysis can be applied to analyze any piece of content that is written or spoken. Content analysis is used in a variety of fields such as politics, human behavior, marketing, literature, health, psychology, and many others.
Content analysis also shows a close relationship between linguistic factors and psychological aspects, which leads to the development of artificial intelligence.
Because content analysis deals with text, numbers, comments, statistics, and many other measurable facts, it is used for forecasting, analyzing trends, and developing logical strategies. It is widely used to eliminate the ambiguity factor and get rid of opinions and assumptions.
What Is Content Analysis?
Content analysis is a research tool used to identify the presence of certain words, themes, or concepts in certain qualitative data (ie, text). Using content analysis, researchers can quantify and analyze the presence, meaning, and relationships of such specific words, themes, or concepts.
For example, researchers can evaluate the language used in a news article to look for bias or bias. Researchers can then make inferences about the message in the texts, the author(s), the audience, and even the culture and time in which the text was set.
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Example Of Content Analysis
For example, let’s say I put in front of you a piece of audio, an old video with a static image, and a document with a lot of text, but no titles or descriptions. In the beginning, you wouldn’t have guessed what it was about.
Let’s say you’re transcribing video and audio recordings onto paper. You then use counting software to count the ten most used words, excluding prepositions (of, over, to, by) and articles (the, a), conjunctions (and, but, or), and other common words like “very.
Your result is that the first 5 words are “candy”, “snow”, “cold” and “sled”. These 5 words appear at least 25 times each, and the next most significant word appears only 4 times. You also find that the words “snow” and “sled” appear next to each other 95% of the time the word “snow” appears.
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What Are The Types Of Content Analysis?
There are two general types of content analysis: conceptual analysis and relational analysis. Conceptual analysis determines the presence and frequency of concepts in the text.
Relational analysis takes conceptual analysis further by examining the relationships between concepts in a text. Each type of analysis can lead to different results, conclusions, interpretations and meanings.
Conceptual Analysis
People usually think of conceptual analysis when they think of content analysis. In conceptual analysis, a concept is selected for research, and the analysis involves quantifying and counting its presence.
The main goal is to check the presence of selected terms in the data. Terms can be explicit or implicit. Explicit terms are easy to define. Coding implicit terms is more difficult: you need to determine the level of implication and base judgments on subjectivity (reliability and validity issues). Thus, the encoding of implicit terms involves the use of a dictionary or contextual translation rules, or both.
To begin a conceptual content analysis, first define a research question and select a sample or samples for analysis. Next, the text needs to be coded into manageable content categories.
It is basically a process of selective reduction. By categorizing the text, the researcher can focus on and code specific words or patterns that inform the research question.
Relational Analysis
Relational analysis begins in the same way as conceptual analysis, when a concept is selected for investigation.
However, analysis involves the study of relationships between concepts. Individual concepts are seen as having no intrinsic meaning, and rather meaning is a product of the relationships between concepts.
To begin relational content analysis, first define a research question and select a sample or samples to analyze. The research question should be focused so that the types of concepts are not subject to interpretation and can be generalized.
Next, select the text to analyze. Carefully select the text to analyze, balancing the availability of sufficient information for careful analysis so that the results are not limited to information that is too large to make the coding process too difficult and difficult to produce meaningful and worthwhile results.
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What Are The Content Analysis Steps?
The analysis method consists of the following steps:
Data Preparation
There are several ways to collect data for qualitative content analysis. However, before starting the analysis, the data must be transformed.
From the set of data that the researcher has collected, the choice of “content” must be clearly defined and justified. Before starting data preparation, the researcher needs to know the answers to the following questions:
- Whether or not to transcribe all data collected.
- Should the verbalization be transcribed verbatim?
- Should observations also be transcribed?
The answers to these questions depend on the objectives of the research. However, everything should be transcribed at the beginning to save time during analysis.
Identifying a unit or topic of analysis
A unit or topic of analysis means classifying content into topics, which can be words, phrases, or sentences. When choosing a unit of analysis, one topic should represent an “idea.”
This means that the data related to the topic should be added to this block. In addition, the section or topics should be based on the objectives of the study.
Development of categories and coding scheme
The next step is to develop subcategories and a coding scheme for analysis. This is derived from three sources: primary data, theories on a similar topic, and empirical research.
Since qualitative content analysis can be based on either an inductive or a deductive approach, categories and codes should be developed based on the approach adopted. In the case of a deductive approach, it is important to relate interpretations to existing theories in order to derive inferences.
However, in the case of the inductive approach, the goal is to develop new theories. Therefore, it is important to evaluate secondary sources to stimulate original ideas. To ensure consistency in codes, categories should be defined according to their properties with examples.
Pre-testing the coding scheme on a sample
As well as quantitative data, qualitative pre-testing data is also important. To ensure consistency, members of the research team should code a sample of the available data. If the level of agreement among researchers is low, recoding should be done again.
Full Text Coding
Once the coding is consistent in the previous step, it is important to apply the coding process to the data.
Assessing the consistency of the coding used
After coding, the validity and reliability of the entire data set must be checked.
Making Inferences Based on Coding or Themes
In this step, you need to make inferences based on the generated codes and categories. It is important to examine properties, parameters, and identify relationships and identify patterns to present the analysis.
Presentation of results
In order to present the results for each topic with conclusions, the results should be supported by secondary data and quotes from the developed code.
In addition, based on the analysis, the researcher can also present the results in the form of graphs, matrices or conceptual frameworks. The results should be presented in such a way that the reader can understand the basis of the interpretations.
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What Is The Goal Of Content Analysis?
The goal of content analysis is to “read between the lines.” It aims to identify answers to questions where the text implies something and is not necessarily explicit.
Content analysis is a study that can analyze human communication, how people plan their lives, what people know about something, and how people react to something.
Content analysis became an alternative to traditional mass media surveys, which were then used to research public opinion.
Content analysis uses methods of studying data, images, printed text, sounds, social media, articles, books, magazines and the Internet – mainly to understand what people mean, what they allow, and what the information they convey is , speaking of business or society as a whole.
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What Are The Sources Of Content Analysis?
Content analysis forms a bridge between quantitative and qualitative research methods, where some organizational issues that are very difficult to study can be addressed, such as organizational behavior, human resources, and customer concerns.
By analyzing the presence of certain words and text in certain qualitative data, the relationship between words and images, researchers can draw conclusions about many vital aspects such as audience, behavior, culture and satisfaction level.
Data sources for content analysis are mainly of two types:
Offline
Offline content analysis is based on books, journals, essays, interviews, research notes, open-ended questions, and reference books. A selection from offline sources will represent the entire universe. However, in many cases offline data may be out of date.
Online
With the rapid development of the Internet, online data sources have gained importance. Online conversations, social media comments, product reviews and customer feedback are collected from the most recent and updated links, making the data source more relevant.
CONCLUSION
Any content analysis project can be approached in one of two ways: inductively or deductively. If the researcher does not know exactly what he is looking for in the text, he will use an inductive approach to explore the text and look for ideas about what concepts or patterns he should investigate.
In addition, the researcher can clearly focus his research and know in advance what type of ideas, behaviors or attitudes he wants to find in the text. In this second situation, a deductive approach will be used to analyze the content.
Content analysis is non-intrusive because it only examines human language. It doesn’t take a lot of money to do content analysis because it can be done manually.
However, software programs exist to help researchers organize their data and, if desired, automatically code their qualitative data. And because content analysis breaks down the source text into a stream of codes, researchers can generate quantitative data (based on numbers) that can be analyzed statistically.
CONTENT ANALYSIS FAQs
What Is Content Analysis Used For?
Researchers use content analysis to learn about the goals, messages, and implications of communication content. They can also make inferences about the producers and audiences of the texts they are analyzing.
Content analysis can be used to quantify the occurrence of certain words, phrases, subjects, or concepts in a set of historical or contemporary texts.
How Is Measurement Of Content In Content Analysis Based?
Content measurement in content analysis is based on structured observation, which is systematic observation based on certain written rules. These rules detail how content should be classified. The categories defined for analysis must be mutually exclusive. These written rules help facilitate replication as well as improve reliability.
What Is Sampling Validity In Content Analysis?
Sampling validity refers to the verification and validation of the sample selected for analysis. Checks semantic validity to see if different phrases or words in a category have similar meanings and to make sure they all belong to the same category. Correlation should also be checked to see if one metric can be substituted for another.
