Science Mapping

Science Mapping

Chaomei Chen (Drexel University, USA), Rachael Dubin (Drexel University, USA) and Timothy Schultz (Drexel University, USA)
Copyright: © 2015 |Pages: 14
DOI: 10.4018/978-1-4666-5888-2.ch410

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In the scientific literature and in our society more broadly, we are increasingly presented with an overwhelming volume of information that challenges our ability to keep abreast of current events and the state of the art. In addition to text-based information retrieval tools like Google Scholar and PubMed, one frequently used metric in science mapping is citation. A citation to a published article is often seen as a sign that the article is potentially useful to the scientific community. A citation does not even have to be positive or supportive to be considered as an impact indicator because, after all, a citation shows that the scientific community cannot simply choose to ignore the work. In this sense, any citations are good citations. The worst-case scenario for a scientific publication is that no one found it worthwhile to cite. The role of citation data in science mapping is that citations provide insights to how published articles are valued by the scientific community. Analyzing topics and language patterns in scientific literature alone is unlikely to reveal this type of evaluative insight. In this article, we will primarily focus on outlining the foundation of citation-based science mapping.

Quantitative studies of scientific literature belong to a field called scientometrics, which is part of the broad discipline of information science and technology. Scientific literature is not only large in size but also complex and dynamic. The fundamental principle of science mapping is to represent the body of scientific literature in a tangible form so that one can handle it more effectively. A science map provides an overview of the scientific landscape which can be used to support exploration, description, or explanation of the state and development of scientific knowledge and practices. We can visualize the relationships between these features at different levels of granularity, investigating direct links between individual works, conceptual relations between groups of articles, similarities between authors, and connections among larger scholarly organizations such as journals and institutions.

Key Terms in this Chapter

Co-Citation: Two articles cited together by the third article.

Citation: A reference made to a published article by a subsequently published article.

Science Mapping: the development and application of computational techniques to the visualization, analysis, and modeling of a broad range of scientific and technological activities as a whole.

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