|Annual Meeting Contributed Papers 2009||START Conference Manager|
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 White & McCain (1998) and Zhao & Strotmann (2008a, b), we mapped out the structure of research in IS for two consecutive periods: 1996-2005 and 2006-2008. We focus on mapping the content of scientific publications from their titles and abstracts. The labels of clusters are 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 (1996-2005) evolved into general web studies in the second period, integrating more aspects of IR research. Hence web studies and IR are more and more interwoven. There is still persistence of user studies in IS but now dispersed among the web studies pole and the IR pole. 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 “information science” continue to occupy a smaller but persistence place. Citation studies remains a monolithic block, isolated from the two other poles (IR and web studies) save for a tenuous link through user studies. Citation studies has also recently evolved internally to accommodate newcomers like “h-index, google scholar and the open access model”. All these results were automatically generated by our method without resorting to manual labeling of specialties nor reading of 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.
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