Search (9 results, page 1 of 1)

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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

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Date

22. 2.2003 17:25:39
22. 2.2003 18:13:11

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Date

22. 2.2003 17:25:39
22. 2.2003 18:20:07

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Abstract

Describes a study of individuals' spatial navigation strategies and a number of performance and preference measures with regard to the design of a 3D visualisation. The underlying semantic space of the user interface consists of a collection of papers from the 3 most recent ACM SIGCHI conference proceedings, visualised as a virtual reality network. This network was automatically constructed based on semantic similarities derived from latent semantic analysis. The project studied the search strategies and general preferences of 11 subjects who used this system to find papers on various topics. The findings should be valuable for designers and evaluators of 3D user interfaces. The results highlight the importance of structural elements in the design of a semantically based user interface, because search strategies of users relied heavily on these mechanisms in the design. Describes the implications for user interface design based on users' psychological models of a semantic space

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Abstract

Introduces a generic approach to the development of hypermedia information systems. Emphasises the role of intrinsic inter-document relationships in structuring and visualising a large hypermedia information space. Illustrates the use of this approach based on 3 types of similarity measurements: hypertext linkage, content similarity and usage patterns. Salient patterns in these relationships are extracted and visualised in a simle and intuitive associated network. The spatial layout of a visualisation is optimised such that closely related documents are placed near to each other and only those intrinsic connections among them are shown to users as automatically generated virtual links. Supports self-organized information space transformation based on usage patterns and othe feedback such that the visual strucutre of the information space is incrementally tailored to users' search and browsing styles

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Abstract

In this article we demonstrate the use of an integrative approach to visualizing and tracking the development of scientific paradigms. This approach is designed to reveal the long-term process of competing scientific paradigms. We assume that a cluster of highly cited and cocited scientific publications in a cocitation network represents the core of a predominant scientific paradigm. The growth of a paradigm is depicted and animated through the rise of citation rates and the movement of its core cluster towards the center of the cocitation network. We study two cases of competing scientific paradigms in the real world: (1) the causes of mass extinctions, and (2) the connections between mad cow disease and a new variant of a brain disease in humans-vCJD. Various theoretical and practical issues concerning this approach are discussed.

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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.

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Abstract

Retracting published scientific articles is increasingly common. Retraction is a self-correction mechanism of the scientific community to maintain and safeguard the integrity of scientific literature. However, a retracted article may pose a profound and long-lasting threat to the credibility of the literature. New articles may unknowingly build their work on false claims made in retracted articles. Such dependencies on retracted articles may become implicit and indirect. Consequently, it becomes increasingly important to detect implicit and indirect threats. In this article, our aim is to raise the awareness of the potential threats of retracted articles even after their retraction and demonstrate a visual analytic study of retracted articles with reference to the rest of the literature and how their citations are influenced by their retraction. The context of highly cited retracted articles is visualized in terms of a co-citation network as well as the distribution of articles that have high-order citation dependencies on retracted articles. Survival analyses of time to retraction and postretraction citation are included. Sentences that explicitly cite retracted articles are extracted from full-text articles. Transitions of topics over time are depicted in topic-flow visualizations. We recommend that new visual analytic and science mapping tools should take retracted articles into account and facilitate tasks specifically related to the detection and monitoring of retracted articles.

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Date

22. 3.2013 19:50:00