Search (26 results, page 1 of 2)

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Date

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

Series

Lecture notes in computer science; 2539

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Date

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

Series

Lecture notes in computer science; 2539

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Abstract

Although it is commonly expected that the citation context of a reference is likely to provide more detailed and direct information about the nature of a citation, few studies in the literature have specifically addressed the extent to which the information in different parts of a scientific publication differs. Do abstracts tend to use conceptually broader terms than sentences in a citation context in the body of a publication? In this article, we propose a method to analyze and compare latent topics in scientific publications, in particular, from abstracts of papers that cited a target reference and from sentences that cited the target reference. We conducted an experiment and applied topical modeling techniques to full-text papers in eight biomedicine journals. Topics derived from the two sources are compared in terms of their similarities and broad-narrow relationships defined based on information entropy. The results show that abstracts and citation contexts are characterized by distinct sets of topics with moderate overlaps. Furthermore, the results confirm that topics from abstracts of citing papers have broader terms than topics from citation contexts formed by citing sentences. The method and the findings could be used to enhance and extend the current methodologies for research evaluation and citation evaluation.

Date

22. 3.2013 19:50:00

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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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Abstract

Presents results of the empirical study of whether skills and knowledge might be transferable between hypermedia systems as is the case with conventional paper based materials. In order to facilitate better understanding of the study, provides comments and information on the 2 multimedia encyclopedias studied: Microsoft's 'Encarta'; and 'The Grolier Multimedia Encyclopedia'

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Abstract

The practical significances of identifying and accomodating individual differences has been established across a number of fields of research. There is a renewed interest in individual differences due to the advances in virtual environments, especially through far-reaching technologies such as information visualization and 3D graphical user interfaces on the WWW. The effects of individual differences on the use of these new technologies are yet to be found out. More fundamentally, theories and methods developed for the earlier generations of information systems are subject to a close examination of their applicability, efficiency, and effectiveness. In this article, we present a brief historical overview of research in in individual differences in the context of virtual environments. In particular, we highlight the notion of structure in the perception of individual users of an information system and the role of individuals' abilities to recognize and use such structures to perform various information-intensive tasks. Striking the balance between individuals' abilities and the demanding task for detecting, understanding, and utilizing such structures is an emerging theme across the 5 articles in this special issue. We outline the approaches and the major findings of these articles with reference to this central theme

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Abstract

Cocitation and co-word methods have long been used to detect and track emerging topics in scientific literature, but both have weaknesses. Recently, while many researchers have adopted generative probabilistic models for topic detection and tracking, few have compared generative probabilistic models with traditional cocitation and co-word methods in terms of their overall performance. In this article, we compare the performance of hierarchical Dirichlet process (HDP), a promising generative probabilistic model, with that of the 2 traditional topic detecting and tracking methods-cocitation analysis and co-word analysis. We visualize and explore the relationships between topics identified by the 3 methods in hierarchical edge bundling graphs and time flow graphs. Our result shows that HDP is more sensitive and reliable than the other 2 methods in both detecting and tracking emerging topics. Furthermore, we demonstrate the important topics and topic evolution trends in the literature of terrorism research with the HDP method.

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Abstract

This article presents 2 studies concerning the role of individual differences in searching through a spatial-semantic virtual environment. In the first study, 10 subjects searched for 2 topics through a spatial user interface of a semantic space. A strong positive correlation was found between associative memory (MA-1) and search performance (r=0,855, p=0,003) but no significant correlation was found between visual memory (MV-1) and search performance. In the secon study, 12 subjects participated in a within-subject experimental design. The same spatial user interface and a simple textual user interface were used. The effects of spatial ability (VZ-2), associative memory (MA-1), and on-line experience were tested on a set of interrelated search performance scores. A statistically significant main effect of on-line experience was found, F(6,4)=6,213, p=0,049, two-tailed. In particular, on-line experience has a significant effect on the recall scores with the textual interface. Individuals experienced in on-line esearch are more likely to have a higher recall score with the textual interface than less experienced individuals. No significant main effects were found for spatial ability and associative memory. Subjects' comments suggest a potentially complex interplay between individuals' mental models and the high-dimensional semantic model. Qualitative and process-oriented studies are, therefore, called for to reveal the complex interaction between individuals' cognitive abilities, doamin knowledge, and direct manipulation skills. A recommendation is made that spatial-semantic models should be adaptable to suit individuals and tasks at various levels

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Abstract

Finding relevant publications is a common task. Typically, a researcher browses through a list of publications and traces additional relevant publications. When relevant publications are identified, the list may be expanded by the citation links of the relevant publications. The information needs of researchers may change as they go through such iterative processes. The exploration process quickly becomes cumbersome as the list expands. Most existing academic search systems tend to be limited in terms of the extent to which searchers can adapt their search as they proceed. In this article, we introduce an adaptive visual exploration system named PaperPoles to support exploration of scientific publications in a context-aware environment. Searchers can express their information needs by intuitively formulating positive and negative queries. The search results are grouped and displayed in a cluster view, which shows aspects and relevance patterns of the results to support navigation and exploration. We conducted an experiment to compare PaperPoles with a list-based interface in performing two academic search tasks with different complexity. The results show that PaperPoles can improve the accuracy of searching for the simple and complex tasks. It can also reduce the completion time of searching and improve exploration effectiveness in the complex task. PaperPoles demonstrates a potentially effective workflow for adaptive visual search of complex information.

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Abstract

This paper discusses some problems encountered in hypermedia-based collaboration and reuse, and presents a conceptual framework to resolve these problems. Three suggestions are made based on the discussion: (1) extra organizational structures are necessary in shared hypermedia to support collaborative interactions; (2) an abstract schema is a key to capture the dynamic nature of the shared hypermedia; (3) an integration of the schema evolution approach and the workflow approach is recommended for an open system hypermedia teamwork support. The whole authoring environment is divided into several component spaces with particular respect to the Dexter Hypertext Reference Model. Not only can this separation reduce the overall complexitiy of working within such an environment, but it also conforms more closely with human cognitive needs in collaborative authoring and reuse activities

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Abstract

Investigates information-seeking tasks and associated cognitve issues in the context of interacting with an evolving collaborative hypertext. Fishexe view browsers were used to facilitate exploring in a large information space. The fishexe view browser was extended to incorporate word frequencies. The effects of the fisheye view browser and the changing document were tested with 2x2 factorial experiment. Multivariate tests founs a significant interaction between the 2 factors and a significant main effect of the fisheye view browser. The users who had access to the word frequency information performed their tasks more effectively than the users without access to word frequencies. This work implies that several aspects of an evolving hypertext might als be useful incorporated in an associated fishexe view browser

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Abstract

Knowledge domain visualization is a visual exploratory approach to the study of the development of a knowledge domain. In this study, we focus an the practical issues concerning modeling and visualizing scientific revolutions. We study the growth patterns of specialties derived from citation and cocitation data an string theory in physics. Special attention is given to the two superstring revolutions since the 1980s. The superstring revolutions are visualized, animated, and analyzed using the general framework of Thomas Kuhn's structure of scientific revolutions. The implications of taking this approach are discussed.

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Abstract

Domain visualization is one of the new research fronts resulted from the proliferation of information visualization, aiming to reveal the essence of a knowledge domain. Information visualization plays an integral role in modeling and representing intellectual structures associated with scientific disciplines. In this article, the domain of computer graphics is visualized based on author cocitation patterns derived from an 18-year span of the prestigious IEEE Computer Graphics and Applications (1982-1999). This domain visualization utilizes a series of visualization and animation techniques, including author cocitation maps, citation time lines, animation of a highdimensional specialty space, and institutional profiles. This approach not only augments traditional domain analysis and the understanding of scientific disciplines, but also produces a persistent and shared knowledge space for researchers to keep track the development of knowledge more effectively. The results of the domain visualization are discussed and triangulated in a broader context of the computer graphics field

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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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Content

We investigate the influence of culture and identity (geographic location) on the constitution of a specific research field. Using as case study the Sloan Digital Sky Survey (SDSS) project in the Astronomy field, we analyzed texts from bibliographic records of publications along three cultural and geographic axes: US only publications, non-US publications and international collaboration. Using three text mining systems (CiteSpace, TermWatch and PEx), we were able to automatically identify the topics specific to each cultural and geographic region as well as isolate the core research topics common to all geographic zones. The results tended to show that US-only and non-US research in this field shared more commonalities with international collaboration than with one another, thus indicating that the former two (US-only and non-US) research focused on rather distinct topics.

Series

Advances in knowledge organization; vol.11

Source

Culture and identity in knowledge organization: Proceedings of the Tenth International ISKO Conference 5-8 August 2008, Montreal, Canada. Ed. by Clément Arsenault and Joseph T. Tennis

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Abstract

This chapter reviews visualization techniques that can be used to map the ever-growing domain structure of scientific disciplines and to support information retrieval and classification. In contrast to the comprehensive surveys conducted in traditional fashion by Howard White and Katherine McCain (1997, 1998), this survey not only reviews emerging techniques in interactive data analysis and information visualization, but also depicts the bibliographical structure of the field itself. The chapter starts by reviewing the history of knowledge domain visualization. We then present a general process flow for the visualization of knowledge domains and explain commonly used techniques. In order to visualize the domain reviewed by this chapter, we introduce a bibliographic data set of considerable size, which includes articles from the citation analysis, bibliometrics, semantics, and visualization literatures. Using tutorial style, we then apply various algorithms to demonstrate the visualization effectsl produced by different approaches and compare the results. The domain visualizations reveal the relationships within and between the four fields that together constitute the focus of this chapter. We conclude with a general discussion of research possibilities. Painting a "big picture" of scientific knowledge has long been desirable for a variety of reasons. Traditional approaches are brute forcescholars must sort through mountains of literature to perceive the outlines of their field. Obviously, this is time-consuming, difficult to replicate, and entails subjective judgments. The task is enormously complex. Sifting through recently published documents to find those that will later be recognized as important is labor intensive. Traditional approaches struggle to keep up with the pace of information growth. In multidisciplinary fields of study it is especially difficult to maintain an overview of literature dynamics. Painting the big picture of an everevolving scientific discipline is akin to the situation described in the widely known Indian legend about the blind men and the elephant. As the story goes, six blind men were trying to find out what an elephant looked like. They touched different parts of the elephant and quickly jumped to their conclusions. The one touching the body said it must be like a wall; the one touching the tail said it was like a snake; the one touching the legs said it was like a tree trunk, and so forth. But science does not stand still; the steady stream of new scientific literature creates a continuously changing structure. The resulting disappearance, fusion, and emergence of research areas add another twist to the tale-it is as if the elephant is running and dynamically changing its shape. Domain visualization, an emerging field of study, is in a similar situation. Relevant literature is spread across disciplines that have traditionally had few connections. Researchers examining the domain from a particular discipline cannot possibly have an adequate understanding of the whole. As noted by White and McCain (1997), the new generation of information scientists is technically driven in its efforts to visualize scientific disciplines. However, limited progress has been made in terms of connecting pioneers' theories and practices with the potentialities of today's enabling technologies. If the difference between past and present generations lies in the power of available technologies, what they have in common is the ultimate goal-to reveal the development of scientific knowledge.

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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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Abstract

Using the option Analyze Results with the Web of Science, one can directly generate overlays onto global journal maps of science. The maps are based on the 10,000+ journals contained in the Journal Citation Reports (JCR) of the Science and Social Sciences Citation Indices (2011). The disciplinary diversity of the retrieval is measured in terms of Rao-Stirling's "quadratic entropy" (Izsák & Papp, 1995). Since this indicator of interdisciplinarity is normalized between 0 and 1, interdisciplinarity can be compared among document sets and across years, cited or citing. The colors used for the overlays are based on Blondel, Guillaume, Lambiotte, and Lefebvre's (2008) community-finding algorithms operating on the relations among journals included in the JCR. The results can be exported from VOSViewer with different options such as proportional labels, heat maps, or cluster density maps. The maps can also be web-started or animated (e.g., using PowerPoint). The "citing" dimension of the aggregated journal-journal citation matrix was found to provide a more comprehensive description than the matrix based on the cited archive. The relations between local and global maps and their different functions in studying the sciences in terms of journal literatures are further discussed: Local and global maps are based on different assumptions and can be expected to serve different purposes for the explanation.

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Abstract

Using visual analytic systems effectively may incur a steep learning curve for users, especially for those who have little prior knowledge of either using the tool or accomplishing analytic tasks. How do users deal with a steep learning curve over time? Are there particularly problematic aspects of an analytic process? In this article we investigate these questions through an integrative study of the use of CiteSpace-a visual analytic tool for finding trends and patterns in scientific literature. In particular, we analyze millions of interactive events in logs generated by users worldwide over a 14-month period. The key findings are: (i) three levels of proficiency are identified, namely, level 1: low proficiency, level 2: intermediate proficiency, and level 3: high proficiency, and (ii) behavioral patterns at level 3 are resulted from a more engaging interaction with the system, involving a wider variety of events and being characterized by longer state transition paths, whereas behavioral patterns at levels 1 and 2 seem to focus on learning how to use the tool. This study contributes to the development and evaluation of visual analytic systems in realistic settings and provides a valuable addition to the study of interactive visual analytic processes.

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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.