Dissertation Information for Yves Khawam
MPACT Status: Fully Complete
Title: Citation patterns in the artificial intelligence journal literature: A study in the determination of an interdisciplinary research base
Abstract: This study proposed to determine whether the disciplines contributing to the journal literature of artificial intelligence (AI) share a common AI research base, or whether their AI research bases are discipline-specific. More precisely, the patterns in which three AI contributing fields (the sciences, social sciences, and humanities) cite themselves and others have been cross-analyzed so as to determine: (1) the differences among the three fields regarding the characteristics of each field's research base and focus within the AI journal literature, and (2) the extent to which that intersecting interdisciplinary area is employed by AI researchers. Hypotheses were analyzed across the three fields on the dependent variables of: field cross-citation rate, field cross-citation diversity, journal citation rate, proceeding citation rate, and age of cited literature, and the interdisciplinary AI research base was mapped out. Principal findings included: (1) the sciences tended to be the most parochial of the three fields in their use of AI literature, and (2) the idea of AI consisting of a completely interdisciplinary endeavor was refuted since the area candidate for an interdisciplinary research base resulted in a maximum extent of 0.1 percent of the research base proper to each field. The implication of such findings is that the overall mission of AI, the movement toward the creation of artificial intelligence, may be undermined by allowing disciplinary fragmentation to cloud the long-term conceptual goals. This study, however, makes no attempt to address this implication, but lays down the ground for it in terms of elucidating the various characteristics of the AI research bases.
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