Content analysis is a qualitative research tool or technique that is used widely to analyze the content and its features. It is an approach used to quantify qualitative information by sorting data and comparing different pieces of information to summarize it into useful information.
Holsti (1969) has defined content analysis as,
“Any technique for making inferences by objectively and systematically identifying specified characteristics of messages.”
The content can vary from a simple word, text, picture to social media data, books, journals, and websites. The objective of content analysis is to present the qualitative content in the form of objective and quantitative information.
In content analysis, qualitative data that is collected for research will be analyzed systematically to convert it into quantitative data. Content analysis is different from the other research, as it does not collect data from people directly. Instead, it is the study of data that is already recorded in social media, text, or books or any other physical or virtual forms.
Content analysis has been used increasingly by organizations to surpass surface-level analysis by using computers and machine learning for automatic labeling and coding of the text.
Example of Content Analysis
Research (Cruz and Lee 2014) was conducted to recognize the challenges that many companies are facing in developing Twitter campaigns. Content analysis was conducted to analyze the Twitter feeds of internationally recognized companies. Various terms were grouped based on Aaker’s five brand personality dimensions framework that is used to describe the traits of a given brand into five dimensions: Sincerity, excitement, competence, sophistication, and ruggedness. Sentiment analysis was also conducted using the Lexicoder Sentiment Dictionary that is used to perform simple content analysis.
The results of the content analysis highlighted two essential factors, word choice and media type, for the success of a marketing campaign on Twitter. These two factors should be taken into consideration while developing a social media marketing plan.
Content analysis has seen rapid growth and acceptance due to the computer-aided text analysis. It has become easier to perform content analysis due to the easy availability of electronic messages, thereby making it easier to analyze with precision and speed.
Content analysis can be dated back to 1920s in the United States of America, where a large quantity of data from mass media such as radio and newspaper was analyzed.
For example, the number of times a text, such as the name of a political party, was repeated in the newspaper was counted and analyzed. However, this was not foolproof as it could not identify the latent meaning, and it just counted the number of times a word repeated.
Later in 1972, Jurgen Ritsert developed a process that was able to identify the latent meaning and ideological contents by applying quantitative analysis. Ever since then, content analysis has been used to interpret the text and to arrive at a valid conclusion
With the advent of the internet and technological advancement, content analysis has gained particular significance. Over the years, many things have changed, and a few have remained constant. Computers are now used to gather, analyze, and present a massive amount of data with lightning speed and accuracy.
Content analysis of the big data produced by social media, online content, and mobile devices has taken higher significance. Content analysis has taken over as the most popular method compared to surveys, interviews, and other forms of analysis.
Never has content analysis received more considerable attention in many fields of research than at present. It has been embraced and is extending far and wide into many disciplines.
The purpose of content analysis is to ‘read between the lines.’ It aims to determine answers to questions where the text implies something, and not necessarily explicit.
Content analysis is a research that can analyze human communications, how people plan their lives, what people know about something, and how people react to something.
Content analysis has become an alternative to the traditional inquiries of the mass media, which was then used for public opinion research. The content analysis employs methods to examine the data, images, printed text, sounds, social media, articles, books, journals and the web – mainly to understand what people mean, what people enable and what does the information conveyed by them say to the business or the society at large.
The content analysis helped Nescafé Dolce Gusto to improve their campaign performance by 400%. The goal of content analysis was to find and create a multi-channel marketing strategy that can attract coffee lovers.
They started by conducting content analysis. They rolled out market research into the coffee lover community online. They collected insights from the coffee lovers and used the information to design a suitable marketing campaign that took into account factors such as the taste and needs of the coffee lovers.
As a result of this content analysis, Nescafé Dolce Gusto was able to increase its Facebook engagement by 400%.
The objective of content analysis:
- To Identify the implied aspects of the content
- To sketch the characteristics of the content
- To analyze and present significant findings of content, clearly and effectively
- To simplify unstructured content
- To identify trends and relationships
- To spot the intentions of individuals or groups of people or an institution
- To describe attitudinal and behavioral responses to communications
- To determine the psychological or emotional state of a group of people
- To justify an argument
To summarize, content analysis is conducted to yield inferences from different kinds of content that could be text, pictures, and social media data.
Sources of Content Analysis
Content analysis forms the bridge between quantitative and qualitative research methods, where some of the organizational issues that are very difficult to study, such as the organization behavior, human resources, and customer issues can be considered. By analyzing the presence of certain words and text within a given qualitative data, the relationship of words and pictures, the researchers can make inferences to many vital aspects such as the audience, behavior, culture, and the level of satisfaction.
The sources of data for content analysis are primarily two types:
The offline content analysis is based on books, journals, essays, interviews, research notes, open-ended questions, and directories. The sample from offline sources will represent the whole universe. However, in many cases, offline data can be outdated.
With the rapid growth of the internet, online data sources have acquired significance. The online conversations, social media comments, product reviews, and customer feedback is collected from the most recent and updated references, thereby making the data source more relevant.
Example of Source used for Content Analysis
Social media posts and conversations are a rich source of text data for content analysis. Data can be extracted using tools. The obtained data look
When the data is cleaned up to identify keywords, the result will be much more precise.
With the above information, it will be much easier to analyze the post and take decisions about the next steps.
Uses of Content Analysis
Content analysis can be applied to analyze any piece of content that is written or verbal. Content analysis is involved in a variety of fields such as politics, human behavior, marketing, literature, health, psychology, and much more. Content analysis is also displaying a close relation between the linguistic factors and psychological aspects, thereby leading to the development of artificial intelligence.
Examples of the Uses of Content Analysis
For example, a brand can discover emerging trends with the use of content analysis. Content from online conversations is obtained from various sources such as news, feedbacks, blogs, tickets, online discussion, social media, and reviews. Once the data is available, the data has to be sliced and diced using algorithms and proven mathematical models. Topics, relationships, and tone intensities are analyzed to identify patterns, correlations, and inferences at multiple levels.
As content analysis deals with text, numbers, comments, statistics, and much more measurable facts, it is used for forecasting, trend analysis, and drawing logical strategies. It is used widely to remove the ambiguity factor and to get rid of opinions and guesswork.
Content that you gather is subjective, and hence using it to analyze and define it more quantitatively helps to arrive at decisions. Therefore, content analysis is essential. It has the following benefits:
- Establishes proof of the reliability of the data
- Allows both quantitative and qualitative analysis
- Offers valuable insights into history by analyzing information
- Provides analytical insight into human thought and language
- To Identify the trends and intentions of an individual or a group
- Understands both human behavior and the use of language, and their relationship
The use of content analysis depends on how you use it. For example, when you release an article on your blog page, content analysis will help to understand the further journey.
How many people read it, how many liked it, how many shared it, how many people visited your website after reading your article, and how much sales increased post releasing this article.
When you look at the content analysis reports, you can identify several areas that are doing well and the specific regions where you will have to devote attention to its improvement. All this would not have happened without content analysis.
Content analysis can be performed in three different methods: conventional, directed, and summative. Though there are three different approaches, they intend to understand and analyze the meaning of content. They do have specific differences, which is predominantly in the coding system.
Also called inductive category development, this approach is used when the existing theory or research on any given subject is limited. Here data is used as a source to arrive at categories rather than using any of the pre-existing categories. In this approach, the researches rely entirely on the data to arrive at new insights. Most of the qualitative analysis methods use this approach to study and analyze.
In this approach, research is based on an existing theory. This approach of content analysis is used to validate or further analyze the already existing theory. This method can be done in two ways. One way is to start coding the data based on the predetermined codes from the earlier approach. Another way is to review the existing codes and assign new codes for the text that could not be categorized in the previous method. The directed content analysis aims to focus and extend the pre-existing theory to determine the key concepts.
In this approach, the words of text will be initially counted and compared, followed by further interpretation of the content. The summative content analysis aims at finding the underlying meanings of the text or words. In this approach, the study starts by searching for a particular text and counting the number of times it appears and further tries to understand the fundamental context for the use of the words either explicit or in its indirect terms. Summative content analysis is a nonreactive method of studying the phenomenon of interest.
The approaches of content analysis depend on the research purposes that may need different research designs and various techniques of analysis. The research should take the choice of using a conventional or summative or directed approach after considering the purpose and the methods.