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Chen, C.: Top Ten Problems in Visual Interfaces to Digital Libraries (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:13:11
- Source
- Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
-
Börner, K.; Chen, C.: Visual Interfaces to Digital Libraries : Motivation, Utilization, and Socio-technical Challenges (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:20:07
- Source
- Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
-
Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006)
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- Abstract
- This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
- Date
- 22. 7.2006 16:11:05
-
Liu, S.; Chen, C.: ¬The differences between latent topics in abstracts and citation contexts of citing papers (2013)
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- Date
- 22. 3.2013 19:50:00
-
Chen, C.: Global access to Library of Congress' digital resources : National Digital Library and Internet resources (1996)
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Chen, C.; Ibekwe-SanJuan, F.; Hou, J.: ¬The structure and dynamics of cocitation clusters : a multiple-perspective cocitation analysis (2010)
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- Abstract
- A multiple-perspective cocitation analysis method is introduced for characterizing and interpreting the structure and dynamics of cocitation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Cocitation networks are decomposed into cocitation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a cocitation cluster's members and their citers. The generic method is applied to a three-part analysis of the field of information science as defined by 12 journals published between 1996 and 2008: (a) a comparative author cocitation analysis (ACA), (b) a progressive ACA of a time series of cocitation networks, and (c) a progressive document cocitation analysis (DCA). Results show that the multiple-perspective method increases the interpretability and accountability of both ACA and DCA networks.
-
Ding, W.; Chen, C.: Dynamic topic detection and tracking : a comparison of HDP, C-word, and cocitation methods (2014)
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Chen, C.: Encarta und The Grolier Multimedia Encyclopedia : additional comments from the journal editor (1995)
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Chen, C.; Rada, R.: Interacting with hypertext : a meta-analysis of experimental studies (1996)
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Liu, M.; Bu, Y.; Chen, C.; Xu, J.; Li, D.; Leng, Y.; Freeman, R.B.; Meyer, E.T.; Yoon, W.; Sung, M.; Jeong, M.; Lee, J.; Kang, J.; Min, C.; Zhai, Y.; Song, M.; Ding, Y.: Pandemics are catalysts of scientific novelty : evidence from COVID-19 (2022)
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Chen, C.; Rada, R.: ¬A conceptual model for supporting collaborative authoring and use (1994)
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Chen, C.; Rada, R.; Zeb, A.: ¬An extended fisheye view browser for collaborative writing (1994)
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Chen, C.: Visualizing scientific paradigms : an introduction (2003)
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Chen, C.; Kuljis, J.: ¬The rising landscape : a visual exploration of superstring revolutions in physics (2003)
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Chen, C.; Czerwinski, M.: Spatial ability and visual navigation : an empirical study (1997)
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Chen, C.: Generalised similarity analysis and pathfinder network scaling (1998)
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Chen, C.; Paul, R.J.; O'Keefe, B.: Fitting the Jigsaw of citation : information visualization in domain analysis (2001)
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Chen, C.; Cribbin, T.; Macredie, R.; Morar, S.: Visualizing and tracking the growth of competing paradigms : two case studies (2002)
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Chen, C.; Ibekwe-SanJuan, F.; Pinho, R.; Zhang, J.: ¬The impact of the sloan digital sky survey on astronomical research : the role of culture, identity, and international collaboration (2008)
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Chen, C.: Predictive effects of structural variation on citation counts (2012)
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- Abstract
- A critical part of a scientific activity is to discern how a new idea is related to what we know and what may become possible. As the number of new scientific publications arrives at a rate that rapidly outpaces our capacity of reading, analyzing, and synthesizing scientific knowledge, we need to augment ourselves with information that can effectively guide us through the rapidly growing intellectual space. In this article, we address a fundamental issue concerning what kinds of information may serve as early signs of potentially valuable ideas. In particular, we are interested in information that is routinely available and derivable upon the publication of a scientific paper without assuming the availability of additional information such as its usage and citations. We propose a theoretical and computational model that predicts the potential of a scientific publication in terms of the degree to which it alters the intellectual structure of the state of the art. The structural variation approach focuses on the novel boundary-spanning connections introduced by a new article to the intellectual space. We validate the role of boundary-spanning in predicting future citations using three metrics of structural variation-namely, modularity change rate, cluster linkage, and Centrality Divergence-along with more commonly studied predictors of citations such as the number of coauthors, the number of cited references, and the number of pages. Main effects of these factors are estimated for five cases using zero-inflated negative binomial regression models of citation counts. Key findings indicate that (a) structural variations measured by cluster linkage are a better predictor of citation counts than are the more commonly studied variables such as the number of references cited, (b) the number of coauthors and the number of references are both good predictors of global citation counts to a lesser extent, and (c) the Centrality Divergence metric is potentially valuable for detecting boundary-spanning activities at interdisciplinary levels. The structural variation approach offers a new way to monitor and discern the potential of newly published papers in context. The boundary-spanning mechanism offers a conceptually simplified and unifying explanation of the roles played by commonly studied extrinsic properties of a publication in the study of citation behavior.
