Using Computer-Aided Content Analysis to Map a Research Domain

Abstract

Content analysis is a powerful tool for investigating attitudes expressed in naturally occurring language data. It is a useful tool to help researchers develop an understanding of a specific research field through identifying how particular issues or topics have been conceptualized or where fieldwork can be limited or prohibitive. This is especially true for research on postconflict reconstruction, where large-scale quantitative surveying or metareviews of the literature can be prohibitive. The present study provides a case study of how a particular content analysis software program-Leximancer-was used to map factors associated with institutional legitimacy in postconflict societies. The case of Timor-Leste is used as an example. We examine texts at three levels of discourse: at the academic, official, and primary levels. Results indicate differing perspectives on legitimacy at each level of discourse. This article offers a snapshot of a potential method for understanding how particular topics are conceptualized within a specific research field and can thus help in the development of evaluation methods or data collection instruments.

What Research Says About MOOCs – An Explorative Content Analysis

“…Moreover, it has been shown that computer-aided content analysis is an appropriate method to map out a research domain (see Fisk, Cherney, Hornsey, & Smith, 2012). The software tool creates so-called concept maps (see Figure 3) that display the core concepts within the text body (conceptual analysis) and show how these concepts are related to each other (relational analysis) by recording the frequency with which words co-occur in the text.…”

An analysis of the Australasian Journal of Educational Technology 2013-2017

“…The software automatically identified significant concepts and themes, producing concept maps that show frequency and connectedness (Smith & Humphreys, 2006), which were then analysed by the author. Leximancer reduces time and cost, as well as limiting human bias (Krippendorff, 2013), and is considered to be an appropriate method by which to map out a research domain (Fisk, Cherney, & Hornsey, 2012). Other journal analyses using Leximancer include Distance Education (Zawacki-Richter & Naidu, 2016), and the IJETHE (Marin et al, 2018).…”

The legislative context of prejudice motivated victimisation: perceptions of police legitimacy and citizen decisions to report hate crime incidents

“…Leximancer, as a content analysis tool, provides visual aids for interpretation and has the advantage of reliably analysing text documents due to lack of concerns regarding coder reliability (Fisk, Cherney, Hornsey, & Smith, 2012;Smith & Humphreys, 2006). In the following sections, I will analyse the visual maps related to hate crime legislative frameworks, first conceptually and then relationally by jurisdictions.…”

“…In the subsections below, I will first explore the conceptual structure of the legislative documents and identify the most important co-occurring themes (Fisk et al, 2012). Secondly, I will discuss the Leximancer map in more detail, including themes and relevant concepts in relation to jurisdictional identifiers.…”

“…the Northern Territory and Tasmania). After exploring the original map, I edited concept seeds and changed text processing settings, removing irrelevant concepts and merging closely associated words (see also Fisk et al, 2012). After the editing stage, I included the jurisdictional identifiers onto the map to visualise the differences in hate crime legislation in different Australian jurisdictions.…”