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Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more directly on the text of their published works. In this study we present static and dynamic word-based approaches using vector space modeling, as well as a topic-based approach based on latent Dirichlet allocation for mapping author research relatedness. Vector space modeling is used to define an author space consisting of works by a given author. Outcomes for the two word-based approaches and a topic-based approach for 50 prolific authors in library and information science are compared with more traditional author cocitation analysis using multidimensional scaling and hierarchical cluster analysis. The two word-based approaches produced similar outcomes except where two authors were frequent co-authors for the majority of their articles. The topic-based approach produced the most distinctive map. [ABSTRACT FROM AUTHOR]

Author research impact was examined based on citer analysis (the number of citers as opposed to the number of citations) for 90 highly cited authors grouped into three broad subject areas. Citer-based outcome measures were also compared with more traditional citation-based measures for levels of association. The authors found that there are significant differences in citer-based outcomes among the three broad subject areas examined and that there is a high degree of correlation between citer and citation-based measures for all measures compared, except for two outcomes calculated for the social sciences. Citer-based measures do produce slightly different rankings of authors based on citer counts when compared to more traditional citation counts. Examples are provided. Citation measures may not adequately address the influence, or reach, of an author because citations usually do not address the origin of the citation beyond self-citations. [ABSTRACT FROM AUTHOR]

A longstanding area of study in indexing is the identification of factors affecting vocabulary usage and consistency. This topic has seen a recent resurgence with a focus on social tagging. Tagging data for scholarly articles made available by the social bookmarking Website CiteULike (www.citeulike.org) were used to test the use of inter-indexer/tagger consistency density values, based on a method developed by the authors by comparing calculations for highly tagged documents representing three subject areas (Science, Social Science, Social Software). The analysis revealed that the developed method is viable for a large dataset. The findings also indicated that there were no significant differences in tagging consistency among the three topic areas, demonstrating that vocabulary usage in a relatively new subject area like social software is no more inconsistent than the more established subject areas investigated. The implications of the method used and the findings are discussed. [ABSTRACT FROM AUTHOR]

The authors investigated 11 sports-related query keywords extracted from a public search engine query log to better understand sports-related information seeking on the Internet. After the query log contents were cleaned and query data were parsed, popular sports-related keywords were identified, along with frequently co-occurring query terms associated with the identified keywords. Relationships among each sports-related focus keyword and its related keywords were characterized and grouped using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two approaches were synthesized in a visual context by highlighting the results of the hierarchical clustering analysis in the visual MDS configuration. Important events, people, subjects, merchandise, and so on related to a sport were illustrated, and relationships among the sports were analyzed. A small-scale comparative study of sports searches with and without term assistance was conducted. Searches that used search term assistance by relying on previous query term relationships outperformed the searches without the search term assistance. The findings of this study provide insights into sports information seeking behavior on the Internet. The developed method also may be applied to other query log subject areas. [ABSTRACT FROM AUTHOR]

Session characteristics taken from large transaction logs of three Web search environments (academic Web site, public search engine, consumer health information portal) were modeled using cluster analysis to determine if coherent session groups emerged for each environment and whether the types of session groups are similar across the three environments. The analysis revealed three distinct clusters of session behaviors common to each environment: “hit and run” sessions on focused topics, relatively brief sessions on popular topics, and sustained sessions using obscure terms with greater query modification. The findings also revealed shifts in session characteristics over time for one of the datasets, away from “hit and run” sessions toward more popular search topics. A better understanding of session characteristics can help system designers to develop more responsive systems to support search features that cater to identifiable groups of searchers based on their search behaviors. For example, the system may identify struggling searchers based on session behaviors that match those identified in the current study to provide context sensitive help. [ABSTRACT FROM AUTHOR]

A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed. [ABSTRACT FROM AUTHOR]

Index modeling and computer simulation techniques are used to examine the influence of indexing frequency distributions, indexing exhaustivity distributions, and three weighting methods on hypothetical document spaces in a vector-based information retrieval (IR) system. The way documents are indexed plays an important role in retrieval. The authors demonstrate the influence of different indexing characteristics on document space density (DSD) changes and document space discriminative capacity for IR. Document environments that contain a relatively higher percentage of infrequently occurring terms provide lower density outcomes than do environments where a higher percentage of frequently occurring terms exists. Different indexing exhaustivity levels, however, have little influence on the document space densities. A weighting algorithm that favors higher weights for infrequently occurring terms results in the lowest overall document space densities, which allows documents to be more readily differentiated from one another. This in turn can positively influence IR. The authors also discuss the influence on outcomes using two methods of normalization of term weights (i.e., means and ranges) for the different weighting methods. [ABSTRACT FROM AUTHOR]

Usage and user feedback about a state digital library, in which the developers/designers, content providers, different types of libraries and their staffs, and a variety of user groups represent a loose federation of separate organizations with diverse expectations and needs, are investigated. Through corroboratory evidence from usage statistics of Internet-based database services available through the digital library, responses to a statewide-administered library survey, and a Web-based survey of end users, the authors identify contributing factors for the organizational usability of state digital libraries. The authors refine and enhance an organizational usability model for the unique environment of state digital libraries and identify three modes of interaction (influence, communication, activity) and the challenges each interaction presents: in addressing diverse player needs and expectations; the unequal awareness and training in using state digital libraries; and the lack of sufficient communication channels among players. In addition, the findings highlight the double-edged impact of physical libraries on the state digital library. The term and notion of the "half-life" index-number of literature obsolescence, as well as their borrowing from nuclear physics and adaptation into the literature of literature obsolescence, have up to now been attributed to the librarian Burton and the physicist Kebler and to their famous 1960 journal article. In this article it is documented that (1) Burton and Kebler in their 1960 article were not the first to use the term literature "half-life"; (2) it was not Burton and Kebler who borrowed the conception of "half-life" from nuclear physics and not them who adapted it into the literature of literature obsolescence; (3) in their 1960 article Burton and Kebler first made critical and later ambiguous statements, and finally attributed only "some validity" to the idea of literature half-life; (4) Burton and Kebler stated and... [ABSTRACT FROM AUTHOR]

Investigates the influence of index term distributions and indexing levels on the document called DARE. Areas of information science research; Importance of term distribution on the density of document spaces; Impact of document clusters on different indexing environments.

Presents a visual term discrimination value analysis method which uses a density space within a distance-angle-based visual information retrieval environment. Information visualization; Term discrimination capacity analysis; Term density space analysis; Advantages of the method.

Analyzes Web queries by users of the Excite search engine in order to study actual Web searching by the public in the United States. General interest of users in recreation and entertainment; Modification of queries; Use of advanced search queries; Use of relevance feedback.

Examines how public Web searching has changed from September 16, 1997 to December 20, 1999. Comparative statistics from two studies of Excite queries' data sets; Distribution of sample of queries across subject categories.