CONTENT ANALYSIS

Meaning of Content Analysis

Content analysis is a method of data collection, observation, and social research used to study both the qualitative and quantitative aspects of communications. Rather than observing people’s behaviour directly or interviewing them, researchers analyse the communications people have produced. This includes available materials (such as archival records, documents, books, newspapers, magazines, diaries, and letters) as well as specially produced materials (such as essays or stories written for a specific research problem). The analysis is made objectively and systematically. Objectivity refers to making an analysis on the basis of explicit rules that enable different researchers to obtain the same results from the same documents. Systematic analysis refers to the inclusion or exclusion of content according to consistently applied selection criteria; only materials relevant to the research hypothesis are examined. The word ‘communication’ here refers to “available written material or print media.” The word ‘manifest’ means “which is presented outwardly.” It thus excludes the ‘implied meaning’. The content (in content analysis) may be manifest or latent. The former refers to the visible actual parts of the text as manifested in the document, i.e., sentences, paragraphs, and so on. It involves counting the frequencies of appearance of the research unit. The latter is the underlying or implied meaning conveyed.

Origin and Evolution of Content Analysis

Content analysis, as a method of studying communications, was developed in the United States as a branch of social psychology known as ‘Communications research.’ The science of communication, which covers all forms of communication, whether public or private, including propaganda and advertising, is one of the important branches of the social sciences. Content analysis can be applied to available materials, such as letters, diaries, newspaper articles and editorials, as well as to materials like stories or essays specifically produced for a particular research problem. Prior to the 1940s, content analysis was mostly based on quantitative analysis of documentary materials, focusing on characteristics that could be identified and counted. But since the 1950s, the analysis has become mostly qualitative, focusing on the general impact of the message conveyed by the existing documents. Carter V. Good and Douglas E. Scates visualised that as “the difference is somewhat like that between a casual interview and depth interviewing.”

Definitions of Content Analysis

Various scholars have defined content analysis, often focusing on slightly different aspects (quantitative vs. qualitative) of the same core process. Because several scholars arrived at nearly identical conclusions, their definitions are as follows:

1. According to Berelson (1952, p. 489), content analysis “as a research technique for the objective, systematic and quantitative description of the manifest content of communication.”

2. According to L. Festinger and Daniel Katz “content analysis is a research technique for the objective systematic and qualitative description of the manifest content of communication.”

3. In the words of Fred N. Kerlinger “content analysis, while certainly a method of analysis, is more than that. It is a method of observation. Instead of observing people’s behaviour directly, or asking them to respond to the scales, or interviewing them, the investigator takes the communications that people have produced and asks questions of the communications.”

4. According to Holsti Loomba and North as “any technique for making inferences by systematically and objectively identifying specified characteristics of Message.”

Characteristics of Content Analysis

Gardner (1975, p. 598) has referred to four characteristics of content analysis as follows:

(i) Objectivity, i.e., carrying out analysis on the basis of explicitly formulated rules which will enable two or more persons to obtain the same results from the same documents.

(ii) Systematic, i.e., including and excluding the content or categories according to consistently applied criteria of selection. This eliminates analysis in which only materials supporting the investigator’s hypotheses are examined.

(iii) Generality, i.e., findings must have theoretical relevance. Purely descriptive information about content unrelated to other attributes of content or to the characteristics of the sender or recipient of the communication is of little scientific value.

(iv) Quantification, i.e., the answer to the question(s) raised should be in quantitative terms (Lasswell, Lerner and Pool, 1992). Some scholars (Kaplan and Goldsen, 1949:83) equate the term ‘quantitative’ with ‘numerical', i.e., classifying content in precise numerical terms. This means that inferences must be derived strictly from counts of ‘frequency’. It also means that information should be conveyed as “40 per cent of people or 40 out of 100 people had this opinion”, because it is more precise than the statement “less than half or a large number of people had this opinion”. But others (Lazarsfeld and Barton, 1951) say that ‘qualitativeness’ and ‘quantitativeness’ are not dichotomous attributes but fall along a continuum, i.e., inferences are drawn from combined frequency and non-frequency techniques. Despite the advantages of quantitative methods, the tendency to equate content analysis with tabulation of frequencies has been criticised on a number of grounds:

(1) The most important argument is that such a restriction leads to bias in the selection of problems to be investigated. Undue emphasis is placed on precision at the cost of problem significance.

(2) Another argument is that more meaningful inferences can be drawn by non-quantitative measures. Qualitative analysis is superior in the problems of applied social science.

(3) The proponents of qualitative techniques also question the assumption (of the proponents of quantitative techniques) that for purposes of inference, frequency of assertion is necessarily related to the importance of the assumption. They (proponents of qualitative techniques) say that the single appearance or omission of an attribute in a document may be of more significance than the relative frequency of other characteristics.

(4) Whether stated explicitly or not, even the most rigorously quantitative study uses qualitative techniques at some stage in the research.

Types of Content Analysis

Sanders and Pinhey (1983, pp. 190-197) have suggested five types of content analysis:

1. Word counting analysis

This counts the use of certain keywords across different texts. For example, one can count the words ‘democracy’ and ‘totalitarianism’ to measure the degree of democratisation in five nations: India, America, England, Canada and France in a sample of elite newspapers. The object could be to find out whether there were any blatant differences between the nations as represented by elite newspapers. This may involve several months and numerous codes and analysts. Similarly, terrorism and authoritarianism can be studied in Pakistan, Israel, Afghanistan, etc.

2. Conceptual analysis

A more sophisticated type of word counting involves words grouped into conceptual clusters (ideas) that constitute variables in a research hypothesis. For example, a conceptual cluster may be formed around the idea of DEVIANCE. Words such as “crime,” “delinquency,” “fraud,” “homosexuals,” “corruption,” and “embezzlement” could all be clustered around DEVIANCE. Therefore, whenever any of the words were found in the test, they would automatically be counted as an instance of the idea of DEVIANCE.

Using conceptual analysis, a researcher may seek to identify relationships between public concerns across different sectors of society by analysing newspaper articles that connect one sector to another. For example, in the mid-1960s, the economy was booming, but crime was also rising. During the 1970s, the economy cooled and went downhill into the 1980s, and crime increased again. In the 1960s, when the economy was healthy yet crime was also high, a researcher might hypothesise that there were very few news stories connecting DEVIANCE and ECONOMY, but rather that the connection was probably between DEVIANCE and VALUES. On the other hand, when the economy cooled and unemployment increased, there were probably more news stories that linked DEVIANCE and ECONOMY. To set up a conceptual analysis, we might develop the following clusters:

Deviance: corruption, embezzlement, fraud, cheating, smuggling.

Economy: poverty, unemployment, inflation, devaluation, recession.

Values: tradition, morality, authority, respect.

Using articles as the unit of analysis and words as scoring units, texts would be analysed only in terms of three concepts: DEVIANCE, ECONOMY and VALUES, even though all of the words that made up the concepts would be counted to determine the weight each concept had. Thus, in an article that mentioned five different words from the same conceptual cluster, the concept would be counted as being in the article five times. The following illustration shows how conceptual analysis counts concepts by counting words in each cluster.

Cluster: Economy

Words

Inflation………………………..    4

Crime........................................      5

Unemployment………………..     2

Corruption……………………..    3

Total of concept                              14

This means that the concept ‘economy’ has been used 14 times in the article. Using newspaper articles from a specific period, say, one year, content analysis would indicate that the articles were centred on the concepts of crime, economy, and values.

3. Semantic analysis

In this, the researcher would be interested not only in the types of words used but also in scaling their intensity levels, such as weak and strong words, positive and negative words, and so on. For positive and strong words, a plus (+) score would be used and for negative and weak words, a minus (-) score would be used; for example, love (+2), dislike (-1), and so on. Measuring these positive and negative scores, the community’s feelings can be assessed through content analysis.

4. Evaluation assertion analysis

Suppose relations between labour and entrepreneur are to be analysed during the labour movement through content analysis of newspaper articles. By finding out how one treated the other by use of certain words, it becomes possible to point out conditions that led to the strike.

5. Contextual analysis

The most sophisticated method of quantitative content analysis is mentioned here only to provide the student with the information that the method is available. It has been used to predict future verbal behaviours based on the analysis of known word clusters (concepts) and individual words. That is, by establishing scales for known verbal behaviours, it is possible to establish parameters, or contexts, where the parameters are unknown. In this way, it is possible to understand more fully the meaning of various texts and their implications. Based on this method, researchers were able to explain the actions of various African military leaders by an analysis of stated political policies. Because of the complexities involved in conducting contextual analysis, the student is advised to begin with one of the other forms of content analysis. It is important to understand, in general, what the technique does so that it can be recognised when reading research reports that use it. In a more advanced research course, students may wish to employ the method.

 

Advantages of Content Analysis

1. Content analysis is unobtrusive and therefore has no effects on the respondent.

2. Content analysis can be used when access to the research topic or research units is not possible. In some cases, the research topic might not be currently accessible and cannot be approached through other methods. Content analysis is the only way to generate data.

3. Content analysis does not require respondents and so avoids the various problems often associated with them.

4. The fact that content analysis involves already completed material and no respondents eliminates researcher bias.

5. Accessibility of the research material is a significant advantage. Texts are readily available for testing and re-testing. This is not possible when the human factor is involved in research.

6. Content analysis is a low-cost method compared with other methods, such as surveys.

7. Content analysis entails less bias than other methods, given that text offers information in a neutral form, ready to be researched by the investigator.

Disadvantages of Content Analysis

1. Some documents may not be accessible to the researcher; personal letters and diaries, for instance, might be difficult to obtain.

2. Documents often contain information related to a small proportion of people, and are therefore not representative.

3. Content analysis cannot study unrecorded events: it is therefore restricted to what has been documented.

4. Documents often are not complete; the information may therefore be biased and often unreliable.

5. Content analysis is less suitable for making comparisons than other methods.

6. Content analysis is susceptible to coder bias.