Search (171 results, page 9 of 9)

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Abstract

Conceptualizations of disciplinarity often focus on the social aspects of disciplines; that is, disciplines are defined by the set of individuals who participate in their activities and communications. However, operationalizations of disciplinarity often demarcate the boundaries of disciplines by standard classification schemes, which may be inflexible to changes in the participation profile of that discipline. To address this limitation, a metric called venue-author-coupling (VAC) is proposed and illustrated using journals from the Journal Citation Report's (JCR) library science and information science category. As JCRs are some of the most frequently used categories in bibliometric analyses, this allows for an examination of the extent to which the journals in JCR categories can be considered as proxies for disciplines. By extending the idea of bibliographic coupling, VAC identifies similarities among journals based on the similarities of their author profiles. The employment of this method using information science and library science journals provides evidence of four distinct subfields, that is, management information systems, specialized information and library science, library science-focused, and information science-focused research. The proposed VAC method provides a novel way to examine disciplinarity from the perspective of author communities.

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Abstract

In this article, we use innovative full-text citation analysis along with supervised topic modeling and network-analysis algorithms to enhance classical bibliometric analysis and publication/author/venue ranking. By utilizing citation contexts extracted from a large number of full-text publications, each citation or publication is represented by a probability distribution over a set of predefined topics, where each topic is labeled by an author-contributed keyword. We then used publication/citation topic distribution to generate a citation graph with vertex prior and edge transitioning probability distributions. The publication importance score for each given topic is calculated by PageRank with edge and vertex prior distributions. To evaluate this work, we sampled 104 topics (labeled with keywords) in review papers. The cited publications of each review paper are assumed to be "important publications" for the target topic (keyword), and we use these cited publications to validate our topic-ranking result and to compare different publication-ranking lists. Evaluation results show that full-text citation and publication content prior topic distribution, along with the classical PageRank algorithm can significantly enhance bibliometric analysis and scientific publication ranking performance, comparing with term frequency-inverted document frequency (tf-idf), language model, BM25, PageRank, and PageRank + language model (p < .001), for academic information retrieval (IR) systems.

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Abstract

This article first analyzes library and information science (LIS) research articles published in core LIS journals in 2005. It also examines the development of LIS from 1965 to 2005 in light of comparable data sets for 1965, 1985, and 2005. In both cases, the authors report (a) how the research articles are distributed by topic and (b) what approaches, research strategies, and methods were applied in the articles. In 2005, the largest research areas in LIS by this measure were information storage and retrieval, scientific communication, library and information-service activities, and information seeking. The same research areas constituted the quantitative core of LIS in the previous years since 1965. Information retrieval has been the most popular area of research over the years. The proportion of research on library and information-service activities decreased after 1985, but the popularity of information seeking and of scientific communication grew during the period studied. The viewpoint of research has shifted from library and information organizations to end users and development of systems for the latter. The proportion of empirical research strategies was high and rose over time, with the survey method being the single most important method. However, attention to evaluation and experiments increased considerably after 1985. Conceptual research strategies and system analysis, description, and design were quite popular, but declining. The most significant changes from 1965 to 2005 are the decreasing interest in library and information-service activities and the growth of research into information seeking and scientific communication.

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Abstract

Knowledge organization (KO) and bibliometrics have traditionally been seen as separate subfields of library and information science, but bibliometric techniques make it possible to identify candidate terms for thesauri and to organize knowledge by relating scientific papers and authors to each other and thereby indicating kinds of relatedness and semantic distance. It is therefore important to view bibliometric techniques as a family of approaches to KO in order to illustrate their relative strengths and weaknesses. The subfield of bibliometrics concerned with citation analysis forms a distinct approach to KO which is characterized by its social, historical and dynamic nature, its close dependence on scholarly literature and its explicit kind of literary warrant. The two main methods, co-citation analysis and bibliographic coupling represent different things and thus neither can be considered superior for all purposes. The main difference between traditional knowledge organization systems (KOSs) and maps based on citation analysis is that the first group represents intellectual KOSs, whereas the second represents social KOSs. For this reason bibliometric maps cannot be expected ever to be fully equivalent to scholarly taxonomies, but they are - along with other forms of KOSs - valuable tools for assisting users' to orient themselves to the information ecology. Like other KOSs, citation-based maps cannot be neutral but will always be based on researchers' decisions, which tend to favor certain interests and views at the expense of others.

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Abstract

The citation relationships between publications, which are significant for assessing the importance of scholarly components within a network, have been used for various scientific applications. Missing citation metadata in scholarly databases, however, create problems for classical citation-based ranking algorithms and challenge the performance of citation-based retrieval systems. In this research, we utilize a two-step citation analysis method to investigate the importance of publications for which citation information is partially missing. First, we calculate the importance of the author and then use his importance to estimate the publication importance for some selected articles. To evaluate this method, we designed a simulation experiment-"random citation-missing"-to test the two-step citation analysis that we carried out with the Association for Computing Machinery (ACM) Digital Library (DL). In this experiment, we simulated different scenarios in a large-scale scientific digital library, from high-quality citation data, to very poor quality data, The results show that a two-step citation analysis can effectively uncover the importance of publications in different situations. More importantly, we found that the optimized impact from the importance of an author (first step) is exponentially increased when the quality of citation decreases. The findings from this study can further enhance citation-based publication-ranking algorithms for real-world applications.

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Abstract

Outstanding scholars have generally been regarded as having special influence that enables them to publish articles in top-tier journals and obtain higher levels of research funding. This study proposes that the social effect of an outstanding scholar, which is derived from the halo effect and the Matthew effect, is favorable for the expansion of the scholar's personal research network and will improve that scholar's future research accomplishments. Data for a total of 101 outstanding information systems scholars and 36 ordinary scholars were collected. The definition of an outstanding scholar is based on the quality and quantity of their publications. The results show that the social effect of the outstanding scholars is beneficial for the development of a research network, including 3 types of network structures. In addition, being highly connected with colleagues leads to higher research accomplishments in terms of quantity, while being connected with colleagues from different sub-fields leads to higher research accomplishments in terms of novelty. Additionally, this study found that the social effect of outstanding scholars is a double-edged sword, with both positive and negative impacts on research accomplishments. The findings contribute several theoretical and practical implications for future research.

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Abstract

In this large-scale contribution, we deal with the relationship between properties of cited references of Web of Science articles and the field normalized citation rate of these articles. Using nearly 1 million articles, and three classification systems with different levels of granularity, we study the effects of number of cited references, share of references covered by Web of Science, mean age of references and mean citation rate of references on field normalized citation rate. To expose the relationship between the predictor variables and the response variable, we use quantile regression. We found that a higher number of references, a higher share of references to publications within Web of Science and references to more recent publications correlate with citation impact. A correlation was observed even when normalization was done with a finely grained classification system. The predictor variables affected citation impact to a larger extent at higher quantile levels. Regarding the relative importance of the predictor variables, citation impact of the cited references was in general the least important variable. Number of cited references carried most of the importance for both low and medium quantile levels, but this importance was lessened at the highest considered level.

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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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Date

20. 1.2015 18:30:22

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Abstract

Purpose This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011-2020. It also examines changes in this structure from 2006-2010 through 2011-2015 to 2016-2020. Results will contribute to a better understanding of the information science research field. Design/methodology/approach The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011-2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor. Findings The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011-2015 but shared dominance with information behavior during 2016-2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016-2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011-2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016-2020. Originality/value Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

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Date

20. 1.2015 18:30:22