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Author(s): Chen CM
Title: Searching for intellectual turning points: Progressive knowledge domain visualization
Source: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 101: 5303-5310
Date: 2004 APR 6
Document Type: Journal : Proceedings Paper
DOI: 10.1073/pnas.0307513100
Language: English
Comment:
Address: Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA.
Reprint: Chen, CM, Drexel Univ, Coll Informat Sci & Technol, 3141 Chestnut St,
Philadelphia, PA 19104 USA. E-mail: chaomei.chen@cis.drexel.edu
Author Keywords:
KeyWords Plus: AUTHOR COCITATION ANALYSIS; CO-CITATION; NETWORKS; DECOMPOSITION; GROWTH
Abstract: This article introduces a previously undescribed method progressively visualizing the evolution of a knowledge domain's cocitation network. The method first derives a sequence of cocitation networks from a series of equal-length time interval slices. These time-registered networks are merged and visualized in a panoramic view in such away that intellectually significant articles can be identified based on their visually salient features. The method is applied to a cocitation study of the superstring field in theoretical physics. The study focuses on the search of articles that triggered two superstring revolutions. Visually salient nodes in the panoramic view are identified, and the nature of their intellectual contributions is validated by leading scientists in the field. The analysis has demonstrated that a search for intellectual turning points can be narrowed down to visually salient nodes in the visualized network. The method provides a promising way to simplify otherwise cognitively demanding tasks to a search for landmarks, pivots, and hubs.
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