Content Analysis in Sociology
Content analysis in sociology involves systematically analyzing the content of various forms of communication, such as written, verbal, or visual materials, to identify patterns, themes, and meanings. Researchers use this method to study social phenomena, media representations, and cultural trends. By examining the underlying messages and symbols, content analysis provides insights into societal values, power dynamics, and social structures.
8 Key excerpts on "Content Analysis in Sociology"
eBook - ePubQuantitative Research Methods in Communication
The Power of Numbers for Social Justice
- Erica Scharrer, Srividya Ramasubramanian(Authors)
- 2021(Publication Date)
- Routledge(Publisher)
...17): “Content analysis is a summarizing, quantitative analysis of messages that follows the scientific method (including attention to objectivity-intersubjectivity, a priori design, reliability, validity, generalizability, replicability, and hypothesis testing based on theory) and is not limited as to the types of variables that may be measured or the context in which the messages are created or presented.” Each of these definitions reveals the logic of the scientific method at play in content analysis, as is seen in the definitions’ references to such topics as validity, measurement, assigning numeric values, replicability, and making inferences. The first two definitions include, as well, a reference to the purpose of content analysis: to understand what appears in texts as an important step in knowing why content takes shape and how audiences create, use, respond to and/or make meaning from that content. Using Content Analysis for Social Justice Content analysis research has the potential to lend insights into particular points in history by studying communication forms produced at a moment in time. Simply by describing media content or other sets of communicative content, content analysis research can implicitly reveal a great deal about the context in which that content or those messages were produced and disseminated. What was valued at the time? What was popular? Who was represented? Who was missing? Most hypotheses in content analysis research have to do with studying how one aspect of the content in question relates to another aspect. For example, you might have a hypothesis that predicts that Muslims will be more frequently depicted as threatening in the news compared to non-Muslims. There are two variables at play: (1) whether individuals in the news are Muslim or not and (2) the degree to which individuals are depicted as threatening...
eBook - ePubUsing Research Instruments
A Guide for Researchers
- Peter Birmingham, David Wilkinson(Authors)
- 2003(Publication Date)
- Routledge(Publisher)
...Content analysis is an extremely broad area of research – its coverage includes both quantitative and qualitative approaches to analysis. We begin this chapter by focusing on some of the more common quantitative methods before moving on to discuss qualitative approaches to content analysis. As a research technique, content analysis has been used in a variety of ways and within a number of contexts. It has been successfully used to analyse text and solve issues of disputed authorship of academic papers: the techniques used have included an examination of prior writings and a frequency count of nouns or commonly occurring words to help determine the probability of authorship. In the early 1990s content analysis was used to establish the identity of the ‘anonymous’ author of the fictional text Primary Colors (Foster 1996), and it has also been used, controversially, to help determine how many people actually wrote the plays attributed to Shakespeare (Mostyn 1985). Content analysis can be used as a powerful research tool to determine, from the content of a message, sound inferences concerning the attitude of the speaker or writer. It has been usefully employed as a descriptor of diverse research techniques used for systematically collecting, analysing and making inferences from messages (North et al. 1963). More recently, Krippendorff has stated content analysis to be simply ‘a research technique for making replicable and valid inferences from data to their context’ (1980: 21). Often the message is delivered as a text, or converted to one (for example, an interview transcript may be produced or focus-group notes may be developed). Other examples of texts suitable for content analysis include essays, journal articles, books and chapters in books, discussions, newspaper articles or stories, speeches, conversations and advertisements...
- Bruce B. Frey(Author)
- 2018(Publication Date)
- SAGE Publications, Inc(Publisher)
...Hsiu-Fang Hsieh Hsiu-Fang Hsieh, Hsiu-Fang Sarah Shannon Sarah Shannon Shannon, Sarah Content Analysis Content analysis 392 394 Content Analysis Content analysis is an analytic method used in either quantitative or qualitative research for the systematic reduction and interpretation of text or video data. Data can be generated from a variety of sources including (a) individual or focus group interviews; (b) responses to open-ended survey items; (c) text from social media; (d) printed materials such as research articles, newspapers, or books; (e) video-taped simulations; or (f) naturally occurring conversational events. It is also used in case study research. The aim of content analysis is to describe data as an abstract interpretation. Use of content analysis as a research technique dates to the 1900s when it was used in communication research primarily to describe the quantity (frequency) rather than quality (meaning) of content contained in textual data. Since this early use, qualitative content analysis has gained popularity as a means to interpret data by identifying codes and common themes (manifest content) and then constructing underlying meanings (latent content). Content analysis is estimated to have been used as a qualitative analytic method in more than 3,000 research studies between 2005 and 2015 in such diverse fields as education, business, economics, social work, social science, and health sciences, including nursing, psychology, medicine, rehabilitation, gerontology, and public, environmental, and occupational health. At least three distinct approaches to content analysis have emerged. These approaches differ in terms of study design, sampling decisions, and analytic strategies used, particularly how coding schemes are developed. The selection of approaches to content analysis largely depends on the research purpose and the availability of existing knowledge in the area of interest, particularly related models or theories...
eBook - ePubSocial Research Methods by Example
Applications in the Modern World
- Yasemin Besen-Cassino, Dan Cassino(Authors)
- 2017(Publication Date)
- Routledge(Publisher)
...Recent technological innovations have allowed content analysis to achieve the quantitative rigor demanded by modern social science. Why Content Analysis? Compared to most of the techniques discussed in other chapters, the results of content analysis may seem less compelling. Instead of measuring behaviors or attitudes, researchers are simply looking at what people say or write. How do researchers know if the results will be useful? Why bother with it at all? First, language is important. By looking at what individuals say or write, researchers can examine subjective experiences and intentions in a way that may be impossible with other methods. Much of the research in the social sciences deals with how individuals socialize, communicate, persuade, or stereotype others—all things that can be measured indirectly with surveys or experiments but directly with content analysis. Second, content analysis allows researchers to test hypotheses that other methods may not be able to. Carried out properly, analysis of an individual’s speech can reveal far more about the inner thoughts and cognitive processes of that individual than the person may realize or intend to reveal. It can even tell about the impact of cultural norms on how an individual thinks, acts, and treats others, a process that’s largely opaque to the individual. Third, content analysis allows researchers to study participants who are unavailable or unwilling to be part of a study. There’s no way to assess the effect of past campaign ads on voters without content analysis: the voters who the ads were designed to reach have grown older and possibly died. Similarly, content analysis has been used to look at the speeches of politicians currently in office...
eBook - ePubApplied Communication Research Methods
Getting Started as a Researcher
- Michael Boyle, Mike Schmierbach(Authors)
- 2019(Publication Date)
- Routledge(Publisher)
...“Text” here refers to any material generated by people through some action and stored in an unchanging form; it does not have to involve written language and could include pictures, videos, or music, among other things. These materials are sometimes known as social artifacts. The example of measuring negativity in ads is one case in which content analysis might be used, but there are many others. For example, content analysis could also be used to see whether news programs give more time to Democrats than Republicans, whether advertisements are more likely to show White consumers than those of other races, or whether video games tend to show women as more sexualized than men. Content analysis is even used when researchers want to convert open-ended items from surveys or other research projects into quantitative data describing basic patterns in participant responses. survey → Unit 10 experiment → Unit 9 causality → Unit 2 systematic → Unit 1 variable → Unit 2 open-ended → Unit 7 population → Unit 8 sample → Unit 8 qualitative versus quantitative → Unit 3 reliability → Unit 6 reactive → Unit 7 depth interviews → Unit 12 transcript → Unit 13 Content analysis most frequently involves the same basic process as all systematic research. First, you must identify the population of texts you wish to study and then draw an appropriate sample from that population. Next, you must engage in a systematic process of observation to measure the relevant variables within that population and evaluate whether your measurement approach is effective. Finally, you are left with data (most often quantitative) that can be analyzed the same as any other research outcomes, as we will discuss in a later unit. Content analysis does have certain characteristics that differ from other types of research, though. First, content analysis requires researchers to pay attention to the unitizing of the content, in a way that may be more complex than normal sampling...
eBook - ePubInterdisciplinary Qualitative Research in Global Development
A Concise Guide
- Marco J. Haenssgen(Author)
- 2019(Publication Date)
- Emerald Publishing Limited(Publisher)
...Content analysis can also be an intermediate step for further quantitative analysis. For instance, Bollen, Mao, and Zeng (2011) used sentiment analysis software to categorise qualitative Twitter content according to the mood it expressed, and then used this information to predict stock market performance. Other common applications are the use of content analysis to code and further analyse open-ended survey questions (Julien, 2008). Content analysis more broadly involves identifying the information that you are looking for in your qualitative sources. 1 Imagine that you are exploring a transport case study in the UK. To contextualise investment decisions for bicycle paths, you might screen ministerial minutes to understand when conversations about cycling emerged. In this case, your research focus would require a content analysis of the documents, rather than, say, an analysis of discourses and debates around cycling therein. Content analysis can thus often usefully complement other qualitative analysis techniques to provide relevant contextual information...
eBook - ePub- Gwen Bouvier, Joel Rasmussen(Authors)
- 2022(Publication Date)
- Routledge(Publisher)
...Rather, the data is usually of a qualitative nature; it is created from the beginning through complex, institutional processes in a certain socio-historical context, and understanding it requires interpretation and contextual consideration. Kracauer thus concludes that, because texts are not atomistic phenomena but created and made meaningful in contexts, a qualitative analytical approach is necessary for content analysis research to be able to draw general conclusions. From its establishment in communication studies, the method has since been further developed in various disciplines. This means that there is a certain variation in understanding what the method represents. On the one hand, it is common to come across a precise definition such as that by Schreier (2014: 170), stating that “[q]ualitative content analysis is a method for systematically describing the meaning of qualitative data. … Three features characterize the method: qualitative content analysis reduces data, it is systematic, and it is flexible.” On the other hand, there is also an understanding of QCA as a general, qualitative approach, as evidenced by a widely cited definition from Patton (2002: 453), stating that QCA “is any qualitative data reduction and sense-making effort that takes a volume of qualitative material and attempts to identify core consistencies and meanings.” Based on this latter understanding, it becomes difficult to perceive any difference between qualitative, descriptive methods, such as thematic analysis and QCA. There may thus be a point in trying to follow Schreier (2012, 2014) and develop the specificity of QCA. The historical background and the argument by Kracauer (1952) in favor of QCA indicates that its value lies in recognizing communication as meaning making, and that the analysis allows a combination of systematic procedures and flexibility, countable categories and context-sensitive interpretation...
eBook - ePubUser Research
Improve Product and Service Design and Enhance Your UX Research
- Stephanie Marsh(Author)
- 2022(Publication Date)
- Kogan Page(Publisher)
...20 Content analysis Understanding your qualitative data Table 20.1 Content analysis method summary Skip table Method summary Suitable for data generated from: qualitative methods such as interviews, contextual inquiry, ethnography and diary studies, usability testing and open text field survey questions too. Can be used in agile and lean environments. Use if you want to: identify patterns in qualitative data, and summarize by counting the patterns/various aspects of the content. You can make sense of large amounts of qualitative data. We looked at content testing in Part Two Chapter 8, but content analysis is not limited to whether your written content is effective. Content analysis can offer some techniques to help you start to get a grip on large amounts of semi-structured data (such as quotes, verbatims and first-hand written accounts) and interpret what you have. Content analysis is a way of codifying and categorizing qualitative data. Coding is not a precise science, it’s an interpretative art. To code is to put things in systematic order. The data you are coding will be about human routine, rituals, rules, roles, relationships (Saladaña, 2016). Things to take into account within these are behaviours, emotions, actions, verbatim quotes (Hall, 2019), concepts, interactions, incidents, terminology or phrases used...
