Search (15 results, page 1 of 1)

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Abstract

Presents an extensive domain analysis of information science in terms of its authors. Names of those most frequently cited in 12 key journals from 1972 through 1995 were retrieved from Social SciSearch via Dialog. The top 120 were submitted to author co-citation analyzes, yielding automatic classifications relevant to histories of the field

Source

Journal of the American Society for Information Science. 49(1998) no.4, S.327-355

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Abstract

In their 1998 article "Visualizing a discipline: An author cocitation analysis of information science, 1972-1995," White and McCain used multidimensional scaling, hierarchical clustering, and factor analysis to display the specialty groupings of 120 highly-cited ("paradigmatic") information scientists. These statistical techniques are traditional in author cocitation analysis (ACA). It is shown here that a newer technique, Pathfinder Networks (PFNETs), has considerable advantages for ACA. In PFNETs, nodes represent authors, and explicit links represent weighted paths between nodes, the weights in this case being cocitation counts. The links can be drawn to exclude all but the single highest counts for author pairs, which reduces a network of authors to only the most salient relationships. When these are mapped, dominant authors can be defined as those with relatively many links to other authors (i.e., high degree centrality). Links between authors and dominant authors define specialties, and links between dominant authors connect specialties into a discipline. Maps are made with one rather than several computer routines and in one rather than many computer passes. Also, PFNETs can, and should, be generated from matrices of raw counts rather than Pearson correlations, which removes a computational step associated with traditional ACA. White and McCain's raw data from 1998 are remapped as a PFNET. It is shown that the specialty groupings correspond closely to those seen in the factor analysis of the 1998 article. Because PFNETs are fast to compute, they are used in AuthorLink, a new Web-based system that creates live interfaces for cocited author retrieval an the fly.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.5, S.423-434

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Content

Beitrag eines Themenheftes: The 50th Anniversary of the Journal of the American Society for Information Science. Pt.2: Paradigms, models, and models of information science

Date

17. 1.2000 12:52:26

Source

Journal of the American Society for Information Science. 50(1999) no.12, S.1051-1063

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Abstract

This paper shows that, given co-citation data, Kohonen feature mapping produces results quite similar to those of multidimensional scaling, the traditional mode for computer-assisted mapping of intellectual domains. It further presents a Kohonen feature map based on author co-citation data that links author names to information about them on the World Wide Web. The results bear on a goal for present-day information science: the integration of computerized bibliometrics with document retrieval

Source

Structures and relations in knowledge organization: Proceedings of the 5th International ISKO-Conference, Lille, 25.-29.8.1998. Ed.: W. Mustafa el Hadi et al

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Abstract

In their article "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient," Ahlgren, Jarneving, and Rousseau fault traditional author cocitation analysis (ACA) for using Pearson's r as a measure of similarity between authors because it fails two tests of stability of measurement. The instabilities arise when rs are recalculated after a first coherent group of authors has been augmented by a second coherent group with whom the first has little or no cocitation. However, AJ&R neither cluster nor map their data to demonstrate how fluctuations in rs will mislead the analyst, and the problem they pose is remote from both theory and practice in traditional ACA. By entering their own rs into multidimensional scaling and clustering routines, I show that, despite r's fluctuations, clusters based an it are much the same for the combined groups as for the separate groups. The combined groups when mapped appear as polarized clumps of points in two-dimensional space, confirming that differences between the groups have become much more important than differences within the groups-an accurate portrayal of what has happened to the data. Moreover, r produces clusters and maps very like those based an other coefficients that AJ&R mention as possible replacements, such as a cosine similarity measure or a chi square dissimilarity measure. Thus, r performs well enough for the purposes of ACA. Accordingly, I argue that qualitative information revealing why authors are cocited is more important than the cautions proposed in the AJ&R critique. I include notes an topics such as handling the diagonal in author cocitation matrices, lognormalizing data, and testing r for significance.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.13, S.1250-1259

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Abstract

In Sperber and Wilson's relevance theory (RT), the ratio Cognitive Effects/Processing Effort defines the relevance of a communication. The tf*idf formula from information retrieval is used to operationalize this ratio for any item co-occurring with a user-supplied seed term in bibliometric distributions. The tf weight of the item predicts its effect on the user in the context of the seed term, and its idf weight predicts the user's processing effort in relating the item to the seed term. The idf measure, also known as statistical specificity, is shown to have unsuspected applications in quantifying interrelated concepts such as topical and nontopical relevance, levels of user expertise, and levels of authority. A new kind of visualization, the pennant diagram, illustrates these claims. The bibliometric distributions visualized are the works cocited with a seed work (Moby Dick), the authors cocited with a seed author (White HD, for maximum interpretability), and the books and articles cocited with a seed article (S.A. Harter's "Psychological Relevance and Information Science," which introduced RT to information scientists in 1992). Pennant diagrams use bibliometric data and information retrieval techniques on the system side to mimic a relevancetheoretic model of cognition on the user side. Relevance theory may thus influence the design of new visual information retrieval interfaces. Generally, when information retrieval and bibliometrics are interpreted in light of RT, the implications are rich: A single sociocognitive theory may serve to integrate research on literature-based systems with research on their users, areas now largely separate.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.4, S.536-559

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Abstract

Author searching is traditionally based on the matching of name strings. Special characteristics of authors as personal names and subject indicators are not considered. This makes it difficult to identify a set of related authors or to group authors by subjects in retrieval systems. In this paper, we describe the design and implementation of a prototype visualization system to enhance author searching. The system, called AuthorLink, is based on author co-citation analysis and visualization mapping algorithms such as Kohonen's feature maps and Pathfinder networks. AuthorLink produces interactive author maps in real time from a database of 1.26 million records supplied by the Institute for Scientific Information. The maps show subject groupings and more fine-grained intellectual connections among authors. Through the interactive interface the user can take advantage of such information to refine queries and retrieve documents through point-and-click manipulation of the authors' names.

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Abstract

This study explores the tendency of authors to recite themselves and others in multiple works over time, using the insights gained to build citation theory. The set of all authors whom an author cites is defined as that author's citation identity. The study explains how to retrieve citation identities from the Institute for Scientific Information's files on Dialog and how to deal with idiosyncrasies of these files. As the author's oeuvre grows, the identity takes the form of a core-and-scatter distribution that may be divided into authors cited only once (unicitations) and authors cited at least twice (recitations). The latter group, especially those recited most frequently, are interpretable as symbols of a citer's main substantive concerns. As illustrated by the top recitees of eight information scientists, identities are intelligible, individualized, and wide-ranging. They are ego-centered without being egotistical. They are often affected by social ties between citers and citees, but the universal motivator seems to be the perceived relevance of the citees' works. Citing styles in identities differ: "scientific-paper style" authors recite heavily, adding to core; "bibliographic-essay style" authors are heavy on unicitations, adding to scatter; "literature-review style" authors do both at once. Identities distill aspects of citers' intellectual lives, such as orienting figures, interdisciplinary interests, bidisciplinary careers, and conduct in controversies. They can also be related to past schemes for classifying citations in categories such as positive-negative and perfunctory- organic; indeed, one author's frequent recitation of another, whether positive or negative, may be the readiest indicator of an organic relation between them. The shape of the core-and-scatter distribution of names in identities can be explained by the principle of least effort. Citers economize on effort by frequently reciting only a relatively small core of names in their identities. They also economize by frequent use of perfunctory citations, which require relatively little context, and infrequent use of negative citations, which require contexts more laborious to set

Source

Journal of the American Society for Information Science and technology. 52(2001) no.2, S.87-108

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Abstract

Many authors have posited a social component in citation, the consensus being that the citers and citees often have interpersonal as well as intellectual ties. Evidence for this belief has been rather meager, however, in part because social networks researchers have lacked bibliometric data (e.g., pairwise citation counts from online databases), and citation analysts have lacked sociometric data (e.g., pairwise measures of acquaintanceship). In 1997 Nazer extensively measured personal relationships and communication behaviors in what we call "Globenet," an international group of 16 researchers from seven disciplines that was established in 1993 to study human development. Since Globenet's membership is known, it was possible during 2002 to obtain citation records for all members in databases of the Institute for Scientific Information. This permitted examination of how members cited each other (intercited) in journal articles over the past three decades and in a 1999 book to which they all contributed. It was also possible to explore links between the intercitation data and the social and communication data. Using network-analytic techniques, we look at the growth of intercitation over time, the extent to which it follows disciplinary or interdisciplinary lines, whether it covaries with degrees of acquaintanceship, whether it reflects Globenet's organizational structure, whether it is associated with particular in-group communication patterns, and whether it is related to the cocitation of Globenet members. Results show cocitation to be a powerful predictor of intercitation in the journal articles, while being an editor or co-author is an important predictor in the book. Intellectual ties based an shared content did better as predictors than content-neutral social ties like friendship. However, interciters in Globenet communicated more than did noninterciters.

Source

Journal of the American Society for Information Science and technology. 55(2004) no.2, S.111-126

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Date

22. 2.2003 17:25:39
22. 2.2003 18:16:22

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Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Source

Journal of the American Society for Information Science and Technology. 58(2007) no.4, S.583-605

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Source

Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1083-1096

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Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates