Abstract
We propose a methodology for mapping the research in Information Science (IS) field based on a combined use of symbolic (linguistic) and numeric information. Using the same list of 12 IS journals as in earlier studies on this same topic (White & McCain 1998; Zhao & Strotmann 2008a&b), we mapped the structure of research in IS for two consecutive periods: 1996β2005 and 2006β2008. We focused on mapping the content of scientific publications from the title and abstract fields of underlying publications. The labels of clusters were automatically derived from titles and abstracts of scientific publications based on linguistic criteria. The results showed that while Information Retrieval (IR) and Citation studies continued to be the two structuring poles of research in IS, other prominent poles have emerged: webometrics in the first period (1996β2005) evolved into general web studies in the second period, integrating more aspects of IR research. Hence web studies and IR are more interwoven. There is still persistence of user studies in IS but now dispersed among the web studies and the IR poles. The presence of some recent trends in IR research such as automatic summarization and the use of language models were also highlighted by our method. Theoretic research on βinformation scienceβ continue to occupy a smaller but persistence place. Citation studies on the other hand remains a monolithic block, isolated from the two other poles (IR and web studies) save for a tenuous link through user studies. Citation studies have also recently evolved internally to accommodate newcomers like βhβindex, Google scholar and the open access modelβ. All these results were automatically generated by our method without resorting to manual labeling of specialties nor reading the publication titles. Our results show that mapping domain knowledge structures at the term level offers a more detailed and intuitive picture of the field as well as capturing emerging trends.