This chapter discusses the analysis of qualitative material. There are many types of qualitative analysis. Some approaches are related to specific forms of data, whereas others are more generic in nature. There can also be considerable differences between some forms of qualitative analysis to the extent that they have very little in common with one another. Given this diversity, it is not possible adequately to address every type of analysis, or provide highly detailed instructions for the more common techniques. Hence, the chapter introduces the iterative processes of coding and categorization as well as some of the major types of qualitative analysis. It shows how to identify key concepts in data, and how those concepts can be connected to theory.
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Content Analysis
On the Rise
Leeann Bass and Holli A. Semetko
This chapter explains content analysis, which is a social science research method that involves the systematic analysis of text, media, communication, or information. The source, the message, the receiver, the medium, and the influence of the message are all topics that have been studied using content analysis and in combination with other methods. There are deductive and inductive approaches to content analysis. Two widely cited studies using content analysis take a deductive approach: using predefined categories and variables based on findings and best practices from prior research. Studies taking an inductive approach to content analysis, by contrast, have an open view of the content, usually involve a small-N sample, and are often based on a qualitative approach. Meanwhile, much has been written on methods and approaches to measuring reliability with human coders. Traditional content analysis uses human coders, whereas a variety of software has emerged that can be used to download and score or code vast amounts of textual news data. The chapter then identifies key benefits and challenges associated with new computational social science tools such as text analysis.
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Gary LaFree
This chapter explores open source databases on terrorism. These are created from unclassified, publicly available information retrieved from both print and digital media. The unit of analysis for these databases are events, organizations, or individuals. The advantage of event- and group-level databases is that they are worldwide in scope. In contrast, individual-level databases are more focused on perpetrators in a single country. However, open-source databases can be susceptible to media inaccuracies and government censorship. There is also the issue of a lack of systematic empirical validation. The chapter notes possible improvements that can be made to open-source databases such as better coverage of domestic terrorism, automated coding, use of geo-spatial information, and more detailed data on the effectiveness of countermeasures.