Sociological Content Analysis

Sociological Content Analysis is a systematic research method used in the social sciences to examine the content of various artifacts of human society, such as diaries, newspapers, television shows, and more. This technique allows researchers to gather and analyze data when direct observation or self-reporting is impractical, often due to the sensitive nature of the topics involved. By categorizing and quantifying large volumes of information, content analysis helps uncover patterns and trends related to social and cultural phenomena, including attitudes, beliefs, and behaviors.

Two primary approaches for developing coding schemes in content analysis are the a priori method, where categories are predefined, and the emergent method, where categories develop from a high-level analysis of the data. Ensuring high inter-rater reliability and content validity is crucial for the credibility of the findings, as the interpretations can be influenced by individual biases. While content analysis offers benefits such as unobtrusiveness and the ability to analyze historical data, it does have limitations, including potential biases from researchers and reliance on available communication forms. Overall, this method provides valuable insights into societal trends and the underlying constructs shaping human behavior.

Published in: 2021

By: Wienclaw, Ruth A.

Subject Terms

Sociological Content Analysis

In the social sciences, it is often impossible to gather data through direct observation or experimental manipulation. Frequently, however, usable data can be collected for analysis in such situations through content analysis. This systematic analysis examines the content of artifacts of human society and parses them into explicit, distinct categories. Content analysis enables researchers to relatively quickly and easily reduce large amounts of information into quantifiable data that can be meaningfully analyzed. Two basic approaches are used for developing coding schemes for content analysis: The a priori method and the emergent method. However, no matter which method is used, it is important that the resultant coding scheme have both high inter-rater reliability and content validity in order for the data to be of use for research or theory building. When properly used, content analysis can be an invaluable tool for social science researchers analyzing social and cultural phenomena.

Keywords Content Analysis; Criterion; Experimenter Error; Inter-Rater Reliability; Operational Definition; Qualitative Research; Quantitative Research; Reliability; Secondary Analysis; Statistical Significance; Unobtrusive Research; Validity; Variable

Sociological Content Analysis

Overview

Social science research is concerned with collecting data about a broad array of factors that influence society and the behavior of individuals within society. However, it is not always possible to gather data by directly observing human behavior. In some situations it is not possible to directly measure a dependent variable at all because individuals may feel reluctant or unable to articulate certain feelings or emotions due to their personal sensitivity (e.g., abuse), political incorrectness (e.g., prejudice), or inability to express the feeling in words. This situation is compounded when trying to gain and analyze data about larger segments of society rather than about individuals. Sometimes, a researcher may be interested in measuring and analyzing a broad concept for all of society. It is virtually impossible to directly gather information about the opinions and beliefs of society in general. Further, such concepts tend to be nebulous, and frequently cannot be operationally defined in terms of behaviors. Therefore, more unobtrusive measures must be used. For situations such as these, it is often helpful for the researcher to examine available data in artifacts of human thought and behavior and to extrapolate back to the underlying construct.

Secondary Data Used for Content Analysis

There is a wide range of secondary data that are available to support researchers who desire to study data in human artifacts. Diaries and personal correspondence can be analyzed to determine a subject's state of mind or emotions. Newspaper or periodical articles can be analyzed to determine the state of mind of a sample of individuals on a given subject (e.g., attitudes towards immigration, reaction to local issues). Television shows, movies, music lyrics, or video games can be examined to determine other cultural trends (e.g., attitudes towards violence, acceptance of teenage sex). Information is mined through such sources using a technique called content analysis: The systematic analysis of the content (as opposed to the format) of artifacts of human society (e.g., newspaper, periodicals, diaries) into explicit, distinct categories. The results of content analysis can be used in both quantitative and qualitative research paradigms.

Benefits of Content Analysis

There are a number of reasons use content analysis.

• First, this technique enables researchers to systematically review and analyze large volumes of data in a way that could not be done (or not be done easily) by other methods.

• Second, content analysis allows researchers to extract data from historical artifacts when it is no longer possible to gain information from the subjects themselves (e.g., historical data).

• Third, content analysis can help researchers determine and articulate the focus of individuals, groups, institutions, or society in general. Content analysis is often used for identifying and analyzing trends and patterns in documents. This technique provides researchers with a basis to monitor trends and shifts in public opinion.

There are a number of advantages to using content analysis. First, content analysis has little to no effect on the subject's behavior. Content analysis is performed after the fact on artifacts of human behavior. Therefore, it does not influence that behavior because the artifact of human behavior has already been produced. In addition, content analysis enables researchers to gather data and information on aspects of human behavior within society that could not otherwise be gathered because subjects are unwilling or unable to directly share their attitudes or feelings on a topic.

Disadvantages of Content Analysis

Content analysis is not without its disadvantages. First, since content analysis is typically based on mass communication, it is limited to data that can be disseminated through such sources. In addition, content analysis is subject to the limitations of other data collection techniques that use human raters. The rating criteria for content analysis need to be operationally well-defined a priori to increase the consistency of ratings. However, even when this is done, the criteria used to operationally define constructs may not be universally accepted and, therefore, cannot be replicated or extrapolated. Further, since content analysis is based on subjective criteria, it is relatively easy for experimenter error to influence the results of the analysis. Experimenter error occurs when the influence of the expectations, beliefs, prejudices, or other attitudes of the researcher affect the data collection process and the subsequent interpretation of the results. For example, when performing a content analysis of violence in television shows, a rater who believes that there is a high incidence of violence in children's television shows is likely to find more violent contents in the shows analyzed than is a rater who does not believe this to be true. Such lack of inter-rater reliability means that the content analysis is not valid and, therefore, not usable for the study.

Preparations for Content Analysis

Before beginning a content analysis, several questions must first be answered. As in any research paradigm, the first step that must be taken is to define and bound the problem. For example, if one were interested in the correlation of violence in the media to violence in real life, one might first develop a hypothesis that stated that an increase in violence in television shows watched by adolescents over the past decade has led to an increase in violence committed by adolescents in real life. Before data could be collected to test this hypothesis, however, one would first need to operationally define the terms "television shows," "violence," "media," and "real life." One would need to determine which television shows were most watched by adolescents not only currently, but also a decade ago. The researcher would also need to further define the population of adolescents of interest for the study. For example, the researcher might be only interested in changes in violent acts by inner-city adolescents. Based on this focus, the researcher would then draw sample only from inner-city youth. However, the results of the study could not be extrapolated to include all adolescents. The researcher would also have to operationally define the term "violence." To do this, the researcher could develop a series of non-overlapping criteria to define violence (e.g., harassment, abuse, assault, battery, murder). These terms would need to be operationally defined not only for violence in the real world, but also for rating incidents of violence in television programs. For example, a rating code might include specific categories such as reference to a violent act, showing the aftermath of a violent act, or showing the violent act itself. Once these parameters were defined, the researcher would next train raters on how to rate these criteria in television shows.

Importance of Reliability & Validity

It is important that any coding scheme used in content analysis be both reliable and valid. Reliability is the consistency with which the coding scheme measures whatever it is measuring; validity is the degree to which the coding scheme measures what it is intended to measure. A coding scheme cannot be valid unless it is reliable. For content analysis, the type of reliability of most interest is inter-rater reliability. This is the consistency with which different raters obtain similar results using the same data collection criteria. Frequently, this is done by having the raters who will review the same material rate a sample of the data. Their scores are compared to determine the consistency with which they rate the data. Rater training, revision of the coding scheme, or other methods to improve the inter-rater reliability are then put in place and the process is repeated until an acceptable level of reliability (often 95 percent) is reached. In addition to determining the content validity of the coding scheme, it is also important to determine the content validity of the scheme. Content validity is a measure of how well the rating scheme reflects the concepts that the researcher is trying to assess. Content validation is often performed by experts in an appropriate field of study. For example, criminologists or sociologists could review the coding scheme to make certain that it contained all relevant aspects of the variables in question and that they were appropriately and well defined.

Defining Coding Units

Coding units that can be used by raters can be defined in a number of ways. One way to do this is to define coding units according to naturally occurring or intuitive parameters (e.g., crime references, crime aftermath, crime portrayal). Similarly, coding units could be defined by artificial units defined by the researcher (e.g., length of time crime is discussed/portrayed in the show). In general, there are two approaches to developing a coding strategy for content analysis: Emergent coding and a priori categories. In emergent coding, preliminary categories are examined based on a high-level examination of the data. Multiple raters review the same material and develop preliminary checklists of the content in the data. These lists can then be compared and differences reconciled. The resultant master rating scheme can then be used for coding a sample of the data. Inter-rater reliability of the coding would then be empirically tested. These steps would then be repeated as necessary until the inter-rater reliability was at an acceptable level. The raters would then proceed with the coding of the data with periodic comparisons for quality control. Another way to determine coding categories is through the development of an a priori set of categories agreed upon by experts in the field. As with emergent coding, the categories of a priori coding are revised and refined as necessary. In both cases, the goals of these iterative processes are to maximize mutual exclusivity between categories and to develop as exhaustive a set of categories as possible.

Applications

A Content Study: Children & Television

There are many socializing agents for children, including family, peers, schools, social groups, and various media. Research has found that television is a significant agent of socialization. In particular, research has found that television significantly contributes to the formation of gender roles and the acquisition of various behavior stereotypes including aggression and violence) in children. Further, children can benefit socially from watching educational programming and suffer from watching violent programming. It is theorized that these consequences stem not from television itself, but from the content of the television programs. This theory postulates that television gives children “forceful and compelling images” about the nature of socially approved gender roles, which are often stereotyped, biased, and outdated. Al-Shehab (2008) used content analysis to examine the gender and race representations and stereotypes in Kuwaiti television programs that were specifically intended for children or that included children in the program regardless of the intended audience. The purpose of the research was threefold.

• First, the research was designed to answer questions concerning differences in gender and race representation in children's programming for two television channels (i.e. Kuwaiti national television and Egyptian satellite television).

• Second, the study examined differences in gender role stereotyping in children's television programming between the Kuwaiti and Egyptian channels.

• Third, the study also examined differences in racial stereotyping between children's programming on the Kuwaiti national channel and Egyptian satellite channel (Al-Shehab, 2008).

The Sample

Al-Shehab ran a content analysis on thirty hours (in thirty-minute segments) of children's television programming for each of the two channels. A sample of programs was selected by randomly assigning the thirty-minute program time periods numbers obtained from a random number table. Sixty segments were randomly drawn from the sample pool. The result and sample of programs included drama, cartoons, news, commercials, and interviews. The dependent variables in the study included gender role specifics, gender role in directions, gender role settings, and race interactions. The content analysis found that male characters outnumbered female characters in both the Kuwaiti and Egyptian channels. Further, it was found that “female characters were portrayed less frequently on the Kuwaiti channel.” On the other hand, the Kuwaiti channel also presented a concomitantly greater racial diversity than did the Egyptian channel. A t -test for non-independent samples was run to determine whether the difference between gender and racial composition of characters in children's programming between the two channels was statistically significant (Al-Shehab, 2008).

The Results

The results of the study found that females and some races (e.g., non-whites, Asians) were underrepresented in Kuwaiti national television programming. This led the researcher to hypothesize that children of immigrant residents in Kuwait (particularly girls) may not find sufficient role models on television for appropriate socialization. Further, the researcher concluded that this lack of an appropriate role model on television could result in children from these groups feeling socially inferior or less important. These findings are consistent with previous research in other cultures. In addition, the Kuwaiti channel included more male and nonwhite, non-Arab of characters than the Egyptian channel. The results of the content analysis also suggested that the Egyptian channel presented more stereotypical and traditional role models. In addition, the results show that “the Egyptian channel portrayed more physical and verbal aggression than did the Kuwaiti channel.” However, most of the characters on the Kuwaiti channel were portrayed within narrowly defined gender roles. For example, female characters were often shown needing to be rescued, submissive, dependent, frail, passive, and so forth (Al-Shehab, 2008).

Recommendations Based on the Findings

In general, the findings of the content analysis suggested that the Kuwaiti national channel underrepresented women and other races when compared with the Egyptian satellite channel. Similarly, both the Kuwaiti national channel and Egyptian satellite channel tend to portray gender and race in highly stereotypical fashion. Based on the findings of the content analysis and on previous research demonstrating the susceptibility of children to the influence of role models on television, the researcher made several suggestions for education in Kuwait. First, it was suggested that children need to be educated early in their lives about the fact that racial and gender stereotypes seen on television are not necessarily true. Specifically, the researcher strongly suggested that parents screen the television programming their children are allowed to watch. Further, the researcher concluded that other socializing agents should emphasize that the stereotypes portrayed on television do not necessarily accurately depict real life. The researcher also suggested racially diverse programming to help socialize children and enable them to keep pace in a multicultural, multiethnic world.

Conclusion

Behavioral and social scientists often encounter situations in which they cannot directly measure the constructs in which they are interested. In some of these cases, however, the researchers can obtain usable, analyzable data by performing a content analysis of various artifacts of human behavior. Content analysis can enable researchers to reduce vast amounts of information available from recorded human artifacts into quantifiable data that can be empirically analyzed. In addition, content analysis has the additional benefit of being unobtrusive and allowing the researcher to collect data without the possibility of contamination resulting from interaction with the subject. There are a number of ways to develop coding schemes for content analysis. No matter which method is used, however, it is important that the resultant scheme be tested for both inter-rater reliability and content validity. If the coding scheme is not both reliable and valid, it will not produce useful or meaningful data.

Terms & Concepts

Content Analysis: The systematic analysis of the content (as opposed to the format) of artifacts of human society (e.g., newspaper, periodicals, diaries) into explicit, distinct categories.

Criterion: A dependent or predicted measure that is used to judge the effectiveness of persons, organizations, treatments, or predictors. The ultimate criterion measures effectiveness after all the data are in. Intermediate criteria estimate this value earlier in the process. Immediate criteria estimate this value based on current values.

Data: (sing. datum) In statistics, data are quantifiable observations or measurements that are used as the basis of scientific research.

Experimenter Error: The influence of the expectations, beliefs, prejudices, or other attitudes of the researcher that may affect the data collection process or the subsequent interpretation of the results.

Inter-Rater Reliability: The consistency with which different raters obtain similar results using the same data collection criteria. Experimenter effects can lead to low inter-rater reliability.

Operational Definition: A definition that is stated in terms that can be observed and measured.

Qualitative Research: Scientific research in which observations cannot be or are not quantified (i.e., expressed in numerical form).

Quantitative Research: Scientific research in which observations are measured and expressed in numerical form (e.g., physical dimensions, rating scales).

Reliability: The degree to which a data collection or assessment instrument consistently measures a characteristic or attribute. An assessment instrument cannot be valid unless it is reliable.

Secondary Analysis: A further analysis of existing data typically collected by a different researcher. The intent of secondary analysis is to use existing data in order to develop conclusions or knowledge in addition to or different from those resulting from the original analysis of the data. Secondary analysis may be qualitative or quantitative in nature and may be used by itself or combined with other research data to reach conclusions.

Statistical Significance: The degree to which an observed outcome is unlikely to have occurred due to chance.

Subject: A participant in a research study or experiment whose responses are observed, recorded, and analyzed.

Unobtrusive Research: An approach to data collection in which the researcher collects data without directly interfacing with the subjects. Unobtrusive research techniques allow the observation of sensitive situations and events or situations in which the presence of the researcher changes the situation. However, unobtrusive research is often far-removed from normal situations.

Validity: The degree to which a survey or other data collection instrument measures what it purports to measure. A data collection instrument cannot be valid unless it is reliable. Content validity is a measure of how well assessment instrument items reflect the concepts that the instrument developer is trying to assess. Content validation is often performed by experts. Construct validity is a measure of how well an assessment instrument measures what it is intended to measure as defined by another assessment instrument. Face validity is merely the concept that an assessment instrument appears to measure what it is trying to measure. Cross validity is the validation of an assessment instrument with a new sample to determine if the instrument is valid across situations. Predictive validity refers to how well an assessment instrument predicts future events.

Variable: An object in a research study that can have more than one value. Independent variables are stimuli that are manipulated in order to determine their effect on the dependent variables (response). Extraneous variables are variables that affect the response but that are not related to the question under investigation in the study.

Bibliography

Al-Shehab, A. J. (2008). Gender and racial representation in children's television programming in Kuwait: Implications for education. Social Behavior and Personality: An International Journal, 36 , 49-63. Retrieved April 28, 2008, from EBSCO Online Database SocINDEX with Full Text. http://web.ebscohost.com/ehost/pdf?vid=5&hid=117&sid=a75388fe-daef-4532-964c-920556ae8f25%40sessionmgr106

Anderson, M. L. & Taylor, H. F. (2002). Sociology: Understanding a diverse society (2nd ed.). Belmont, CA: Wadsworth/Thomson Learning.

Evans, M. P. (2013). Men in counseling: A content analysis of the journal of counseling & development and counselor education and supervision 1981–2011. Journal of Counseling & Development, 91, 467-474. Retrieved October 31, 2013, from EBSCO Online Database SocIndex with Full Text. http://search.ebscohost.com/login.aspx?direct=true&db=sih&AN=90535084

Gambrel, L., & Butler VI, J. L. (2013). Mixed methods research in marriage and family therapy: A content analysis. Journal of Marital & Family Therapy, 39, 163-181. Retrieved October 31, 2013, from EBSCO Online Database SocIndex with Full Text. http://search.ebscohost.com/login.aspx?direct=true&db=sih&AN=86745621

Stemler, S. (2001). An introduction to content analysis. ERIC Digest. Retrieved April 28, 2008, from http://www.ericdigests.org/2002-2/content.htm

Umoquit, M., Peggy, T., Varga-Atkins, T., O'Brien, M., & Wheeldon, J. (2013). Diagrammatic elicitation: defining the use of diagrams in data collection. Qualitative Report, 18, 1-12.Retrieved October 31, 2013, from EBSCO Online Database SocIndex with Full Text. http://search.ebscohost.com/login.aspx?direct=true&db=sih&AN=89736520

Sociological Content Analysis

On this Page

Subject Terms

Sociological Content Analysis

Sociological Content Analysis

Overview

Secondary Data Used for Content Analysis

Benefits of Content Analysis

Disadvantages of Content Analysis

Preparations for Content Analysis

Importance of Reliability & Validity

Defining Coding Units

Applications

A Content Study: Children & Television

The Sample

The Results

Recommendations Based on the Findings

Conclusion

Terms & Concepts

Bibliography

Suggested Reading