ABSTRACT: This chapter presents a practical guide to media analysis, exemplified through a focus on print news media and the topic of homelessness, but outlining principles of qualitative media analysis which are applicable to all media forms. The first section charts our shift in focus, out from media content analysis as a dominant approach to news analysis towards the role of media in society and intergroup relations. The second section offers a broader conceptual outline for understanding and analysing the role of news media depictions, focusing on marginalized groups. The third section provides a worked example of our analysis process, which includes efforts to bring the broader perspective into action. The chapter is completed with some concluding comments.
ABSTRACT: This unit provides the tools necessary to analyze qualitative data by providing different perspectives on how data of different kinds (e.g., texts, transcripts) can be analyzed. A range of approaches are discussed ranging from more directly applied approaches such as identifying themes or using textual analysis to more critical-based approaches such as rhetorical criticism. Grounded theory is discussed as an inductive approach to qualitative data analysis. These provide the reader with a range of options to making sense of their data. The importance of exemplars in presenting qualitative data is also discussed. Research-in-depth and Steps-to-success entries along with activities at the end of the unit provide further opportunity for application of key concepts giving the reader further skills in applying concepts to real-world situation.
ABSTRACT: Due to the rise in processing power, advancements in machine learning, and the availability of large text corpora online, the use of computational methods including automated content analysis has rapidly increased. Automated content analysis is applied and developed across disciplines such as computer science, linguistics, political science, economics and – increasingly – communication science. This chapter offers a theoretical and applied introduction to the method, including promises and pitfalls associated with the method.
ABSTRACT: Content analysis is a research method used to analyze social artifacts such as television shows, newspaper articles, or web sites, among others. An integral part of content analysis research is the coding process, the success of which hinges upon reliable coders – the people who analyse the content. This chapter will cover the basics of the process of conducting content analysis including developing a coding guide, a coding sheet, exploring distinctions between manifest and latent content, as well as establishing and evaluating intercoder reliability. This unit also provides examples to help readers see the ways content analysis can apply to their own research projects.
ABSTRACT: Content analyses sway policy by describing the prevalence of mass media messages and implying effects. However, content-based research focusing ondynamic new media products such as websites, mobile applications, and video games presents methodological challenges. Our team recently conducted a large-scale content analysis exploring food marketing to children across media platforms, in which we captured and analyzed a variety of media-rich content. We consulted multiple sources to form our sampling frame, employed a complex sampling technique to allow for generalization of findings, used screen-capture software to record our exploration of media products, analyzed data using video coding software, and created a custom scale to determine the target audience of certain media products. We believe the steps we have taken may provide valuable insights into aspiring content analysts interested in studying media-rich content and address challenges that have been plaguing content analysts for the past two decades.
ABSTRACT: In this article, we argue that digital media pose such challenges for analysing media content adequately that the established approach does not work as intended, reflecting underlying assumptions inherited from analogue media formats. We review two relatively new forms of the content analysis method—big data and liquid content analysis—and juxtapose these with established content analysis. In addition, we detail how these two methods tackle content analysis pillars such as mode of analysis, sampling, sampling size, variable design, unit of analysis, measuring point(s), access/capture/storing, conclusions/generalizability and the key agent doing the actual work. We summarize the article by arguing that established content analysis is insufficient for digital media but that common standards, protocols and procedures are yet to be developed for these new approaches to digital journalism research.
ABSTRACT: From a general perspective, there are two main differences between quantitative and qualitative content analysis. First, quantitative content analysis works deductively and measures quantitatively. In this respect, quantitative content analysis decomposes the text material into different parts and assigns numeric codes to these elements or parts. Of course, such parts are not just words, but are rather issues, statements, arguments, or bundles of → meaning. By contrast, however, qualitative content analysis works inductively by summarizing and classifying elements or parts of the text material and assigning labels or categories to them. In this respect, qualitative content analysis searches rather for “coherent” meaning structures in the text material. Second, quantitative content analysis can deal with a large quantity of text material. Qualitative content analysis, on the other hand, is limited to a few pieces of text material – whether these are newspaper reports, interview transcripts, or observational protocols. In practical respects, one can say that quantitative content analysis applies category schemas for the purpose of measuring quantitatively, whereas qualitative content analysis develops categories in a qualitative, rather inductive, or hermeneutic, way. Further differences that are emphasized by advocates of qualitative methodology or the qualitative paradigm will be discussed later.
ABSTRACT: Quantitative content analysis is an empirical method used in the social sciences primarily for analyzing recorded human communication in a quantitative, systematic, and intersubjective way. This material can include newspaper articles, films, advertisements, interview transcripts, or observational protocols, for instance. Thus, a quantitative content analysis can be applied to verbal material, and also to visual material like the evening news or television entertainment. Surveys, → observations, and quantitative content analysis are the main three methods of data collection in empirical communication research, with quantitative content analysis the most prominent in the field (Survey). In other disciplines like psychology or sociology quantitative content analysis is not used as widely.
ABSTRACT: The purpose of this research is twofold. Study I assesses content analyses of news (2015–2020) that sampled from databases to see which are used most frequently and to observe how researchers justify and contextualize their database choices. Results indicate that Nexis Uni is the database most commonly employed, and that researchers rarely justify their choice or include mention of database limitations. Next, Study II compares Factiva, Google News, NewsBank, Nexis Uni and ProQuest, finding considerable differences in number of stories, geographic reach, media type and coverage of a specific news event.
ABSTRACT: The aim of this chapter is to offer a critical review of news media coverage of health. The sociology of news production offers valuable analytical insights for studying trends and characteristics of health coverage in the news media, for it addresses various factors that shape health information. In this chapter, news is conceived as the product of a socially constructed reality. Heider (2008), for instance, asserts that the day’s news is a result of many policies, decisions, and circumstances. It is a social process, in part institutional culture, in part human dynamics. As a part of the sociology of news frame-work, one of the main assumptions of this chapter is that the dynamics of news production shape the content of health news, which, in turn, limits the quality of health information.
ABSTRACT: Given the scale of digital communication, researchers face a painful trade-off between powerful, scalable computational strategies, and the theoretical sensitivity offered by small-scale manual analyses. Especially in the study of natural discourse on digital media, the interactive, ever-evolving stream of conversations across multiple platforms regularly defies efforts to obtain well-defined samples of manageable size, while their linguistic variability imposes major limitations upon the accuracy of automated tools. In this paper, we draw upon recent advances in computational text analysis to develop a hybrid approach to the deductive analysis of large-scale digital discourse, which combines the algorithmic extraction of coherent, recurrent patterns with a manual coding of identified patterns. The approach scales up to treat millions of texts at minimal added human effort, while affording researchers close control over the process of theory-guided classification. We demonstrate the power of Hybrid Content Analysis by studying polarization in a quarter of a million contributions from cross-platform interactive social media discourse about a controversial incident.
ABSTRACT: Research in the subfield of media production and content seeks to describe and explain the symbolic world of the media with reference to a variety of contributing societal, institutional, organizational, and normative factors. It draws boundaries around a large and diverse body of research efforts, predominantly social science, but also including more interpretive cultural analysis. If much of the communication field has concerned itself with the effects of media, and the process by which they are produced (→ Media Effects; Exposure to Communication Content), this more recently emerging area has treated the media map of the world itself as problematic, something to be understood and predicted through an awareness of underlying forces. These forces provide the context of “media production,” which is examined for its systematic ties to “content.” Understanding these “messages” that constitute the symbolic environment is an ambitious task, given the multitude of factors influencing the media. But locating these questions within such a conceptual framework has begun to allow the field of communication to devote the same sustained research to the creation, control, and shape of the mediated environment as it has to the effects on audiences of that environment. The same research tools used so extensively to examine media effects can be turned on those media and their links with the culture of other organizations and institutions.
ABSTRACT: In this chapter we describe visual content analysis of journalistic images. In order to answer more complex questions than commonly addressed with visual content analysis, we have developed a coding strategy addressing specific phases of Knieper's (2003) scheme for the process of image communication.
We will first provide a brief overview of quantitative content analysis, its strengths, issues, and limitations. We then describe how Knieper's (2003) scheme of the process of image communication can help to focus visual content analysis appropriately.
ABSTRACT: This chapter discusses media content analysis, a method that applies quantitative and qualitative procedures to make inferences from text. Its main advantages are that it is unobtrusive, and that there is a plethora of media content available and accessible for research. The main challenge of the method is to develop a research design that promises valid inferences from text (meaning that ‘it captures what it sets out to capture’). Ignoring or not addressing such issues is the main reason for ethical concern. This chapter is based on the assumption that aside from more common methods like document analysis and interviews, media content analysis is also a valuable option for the study of media and communication policy. On the one hand, the method can grasp the public discourse about issues of media and communication policy. On the other hand, the data gathered by using this method offers much-needed evidence for policy-making. This chapter provides an overview on the steps of preparing and conducting a media content analysis, from the research design and sampling, to the process of coding, and the analysis of data. Two studies that employed media content analysis to investigate a topic relevant for media and communication policy are used as illustration.