1,842,704 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Author Co-Citation Analysis (ACA): a powerful tool for representing implicit knowledge of scholar knowledge workers
Full text linkIn the last decade, knowledge has emerged as one of the most important and valuable organizational assets. Gradually this importance caused to emergence of new discipline entitled ―knowledge management‖. However one of the major challenges of knowledge management is conversion implicit or tacit knowledge to explicit knowledge. Thus Making knowledge visible so that it can be better accessed, discussed, valued or generally managed is a long-standing objective in knowledge management. Accordingly in this paper author co- citation analysis (ACA) will be proposed as an efficient technique of knowledge visualization in academia (Scholar knowledge workers)
Also By The Same Author: AKTiveAuthor, a Citation Graph Approach to Name Disambiguation
No full textThe desire for definitive data and the semantic web drive for inference over heterogeneous data sources requires co-reference resolution to be performed on those data. In particular, name disambiguation is required to allow accurate publication lists, citation counts and impact measures to be determined. This paper describes a graph-based approach to author disambiguation on large-scale citation networks. Using self-citation, co-authorship and document source analyses, AKTiveAuthor clusters papers, achieving precision of 0.997 and recall of 0.818 over a test group of eight surname clusters
A New Framework for the Citation Indexing Paradigm
Full text linkA new citation indexing paradigm is proposed: the cascading citation indexing framework (c2IF, for short). It improves the way research publications are assessed for their impact in promoting science and technology. Given a collection of articles and their citation graph, citations are considered at the (article, author) level. Each one article is uniquely identified by means of the Digital Object Identifier (DOI, http://www.doi.org). To identify each one author uniquely, a Universal Author Identifier (UAI) scheme is established. In addition to the citations directly made to a given (article, author) pair, citation paths that target each one citing article are also considered. The granularity of the paradigm is further increased by introducing the concept of the chord, whereby a citation path of length one co-exists with paths of length two or higher, involving the same source- and target- articles. The c2IF output emerges in the form
of a medal standings table, analogous to the one that ranks teams at athletic events: when two (article, author) pairs receive the same number of (direct) citations, the one that is cited by more popular articles (i.e. articles that comprise targets to a larger number of paths in the citation graph), is assigned a higher rank value
Co-citation Analysis: An Overview
Full text linkThis article gives an overview of co-citation analysis and its applications in tracking the linkages among the intellectual works and mapping the evolutionary structure of scientific disciplines. It also focuses on the features, interface, terminology used, merits and demerits of co-citation based online database applications
Characteristics of Self-Citation in Journal of Natural Rubber Research 1988-1997: a Ten-Year Bibliometric Study
Full text linkAnalyses the extent of journal self-citation and author self-citation in the research articles and short communications published in Journal of Natural Rubber Research during 1988 to 1997. Results show that 53% of articles contained journal self-citations; the rate of journal self-citations per article ranges between 1 to 12; a high percentage of authors (61.4%) contributing articles to the journal cited themselves; a tendency is noticed for authors affiliated to the institution publishing the journal to cite the journal; the highest self-citing author is A. D. Roberts
Citation chain aggregation: An interaction model to support citation cycling
No full textThis is the postprint version of the conference paper.Citation chaining is a powerful means of exploring the academic literature. Starting from just one or two known relevant items, a
naïve researcher can cycle backwards and forwards through the citation graph to generate a rich overview of key works, authors and journals relating to their topic. Whilst online citation indexes
greatly facilitate this process, the size and complexity of the search space can rapidly escalate. In this paper, we propose a
novel interaction model called citation chain aggregation (CCA). CCA employs a simple three-list view which highlights the
overlaps that occur between the first-generation relations of known relevant items. As more relevant articles are identified, differences in the frequencies of citations made by or to unseen articles provide strong relevance feedback cues. The benefits of this technique are illustrated using a simple case study
Mapping the structure and development of Science using co-citation analysis
Full text linkCo-citation analysis is a unique method used for studying the cognitive structure of science andassessing the research productivity. It is a research tool for examining the intellectual development and structure of the scientific discipline. This paper illustrates principles, techniques and applications of co-citation analysis. It also introduces the newly emerging co-citation analysis softwares,especially SciVal Spotlight and CiteSpace. Co-citation analysis is based on grouping together the papers that are frequently cited in pairs. Combined with single-link clustering and multidimensional scaling techniques, co-citation analysis can literally map the structure of specialized research areas as well as science as a whole
The Development of Social Simulation as Reflected in the First Ten Years of JASSS: a Citation and Co-Citation Analysis
Full text linkSocial simulation is often described as a multidisciplinary and fast-moving field. This can make it difficult to obtain an overview of the field both for contributing researchers and for outsiders who are interested in social simulation. The Journal for Artificial Societies and Social Simulation (JASSS) completing its tenth year provides a good opportunity to take stock of what happened over this time period. First, we use citation analysis to identify the most influential publications and to verify characteristics of social simulation such as its multidisciplinary nature. Then, we perform a co-citation analysis to visualize the intellectual structure of social simulation and its development. Overall, the analysis shows social simulation both in its early stage and during its first steps towards becoming a more differentiated discipline.Citation Analysis, Co-Citation Analysis, Lines of Research, Multidisciplinary, Science Studies, Social Simulation
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