Search (5 results, page 1 of 1)

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Date

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

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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.

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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.

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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