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Content Analysis: Advantages and Disadvantages

Content analysis is a systematic, quantitative process of analyzing communication messages by determining the frequency of message characteristics. Content analysis as a research method has advantages and disadvantages. Content analysis is useful in describing communicative messages, the research process is relatively unobtrusive, and content analysis provides a relatively safe process for examining communicative messages, but it can be time-consuming and presents several methodological challenges. This entry identifies several advantages and disadvantages of content analysis related to the scope, data, and process of content analysis.

Scope

The scope and advantage of content analysis is as a descriptive tool. Content analysis can be used to describe communication messages. Content analysis focuses on the specific communication message and the message creator. It is often said that an advantage of content analysis is that the message is “close to” the communicator; that is, content analysis examines communicative messages either created by or recorded from the communicator. Researchers can examine the manifest (the actual communicative message characteristics) and latent (what can be inferred from the message) content of a message. Researchers can use content analysis to study communication processes over time. For example, a communication scholar might be interested in the metaphors presidential candidates have used in speeches during war time.

While content analysis is used to describe communicative messages, content analysis cannot be used to draw cause-and-effect conclusions. Identifying and describing the characteristics of a message is not enough to make claims of what caused or was caused by a message. Content analysis can, however, be combined with other methods to make causal claims, or the description developed through content analysis can be used as a starting point for future causal research. Describing the messages a mother uses to deny a young child’s request is not sufficient to determine the child’s behavior, but combined with other methods (e.g., experimental methods), the child’s behavior could be predicted.

Data

Content analysis is a beneficial research method because of the advantages in collecting data and analyzing quality data. Content analysis can be applied to various types of text (e.g., advertisements, books, newspaper articles, electronic mail, personal communication), and therefore is useful for studying communication from a variety of different contexts. Many times, content analysis can be conducted on existing texts, and therefore the work of collecting data may be minimal (though searching through decades of newspaper articles is a time-consuming process as well). Since content analysis can be used to study communication processes over time, it is useful for studying historical contexts, because describing messages over time can help researchers identify trends in messages over time and subsequently explore the historical context in which the messages changed.

Content analysis also benefits from the data, or communicative messages, coming from the source, or communicator. Data straight from the source relieves several methodological issues (which will be described in greater detail later in this entry). Additionally, data is often readily available for content analysis. For example, print resources are already in an analyzable format, as is written correspondence. Transcripts of videos and radio shows, music lyrics, and the like are readily accessible on the Internet. Also, many texts (e.g., newspaper, books) are available for public consumption and therefore access to texts is easier, making research using content analysis relatively unobtrusive. Once the message has been shared, the researcher only needs the data, and not the source, to conduct the analysis. This is an important benefit of content analysis, as many analyses can bypass human subjects boards because the research neither involves nor affects actual participants; however, some content analyses require data collection from human sources and must therefore receive appropriate approval before the data is collected and research is conducted. Content analysis also affords researchers richer data; that is, because actual communicative messages are collected and analyzed, researchers are exposed to more detailed data than they could obtain through survey research, for example.

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