460,111 research outputs found
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Sociological implications of scientific publishing: Open access, science, society, democracy and the digital divide
No full textClaims for open access are mostly underpinned with
1. science—related arguments (open access accelerates scientific communication);
2. financial arguments (open access relieves the serials crisis);
3. social arguments (open access reduces the digital divide);
4. democracy—related arguments (open access facilitates participation); and,
5. socio—political arguments (open access levels disparities).
Using sociological concepts and notions, this article focuses strongly on Pierre Bourdieu\u27;s theory of (scientific) capital and its implications for the acceptance of open access, Michel Foucault\u27;s discourse analysis and the implications of open access for the concept of the digital divide. Bourdieu\u27;s theory of capital implies that the acceptance of open access depends on the logic of power and the accumulation of scientific capital. It does not depend on slogans derived from hagiographic self—perceptions of science (e.g., the acceleration of scientific communication) and scientists (e.g., their will to share their information freely). According to Bourdieu\u27;s theory, it is crucial for open access (and associated concepts like alternative impact metrics) to understand how scientists perceive its potential influence on existing processes of capital accumulation and how open access will affect their demand for status. Foucault\u27;s discourse analysis suggests that open access may intensify disparities, scientocentrism and ethnocentrism. Additionally, several concepts from the philosophy of sciences (Popper, Kuhn, Feyerabend) and their implicit connection to the concept of open access are described in this paper
Showing the essential science structure of a scientific domain and its evolution
No full textCategory cocitation and its representation through social networks is proving to be a very adequate technique for the visualization and
analysis of great scientific domains. Its combination with pathfinder networks using pruning values r=∞and q=n−1 makes manifest the essence of research in the domain represented, or what we might call the `most salient structure'. The possible loss of structural information, caused by aggressive pruning in peripheral areas of the networks, is overcome by creating heliocentric maps for each category. The depictions obtained with this procedure become tools of great usefulness in view of their capacity to reveal the evolution of a given scientific domain over time, to show differences and similarities between different domains, and to suggest possible new lines for development. This article presents the scientogram of the United States for the year 2002, identifying its essential structure. We also show the scientograms of China for the years 1990 and 2002, in order to study its particular national evolution.
Finally, we try to detect patterns and tendencies in the three scientograms that would allow one to predict or flag the evolution of a scientific domain
Author Co-Citation Analysis (ACA): a powerful tool for representing implicit knowledge of scholar knowledge workers
No full textIn 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)
A new technique for building maps of large scientific domains based on the cocitation of classes and categories
No full textOur objective is the generation of schematic visualizations as interfaces for scientific domain analysis. We propose a new technique that uses thematic classification (classes and categories) as entities of cocitation and units of measure, and demonstrate the viability of this methodology through the representation and analysis of a domain of great dimensions. The main features of the maps obtained are discussed, and proposals are made for future improvements and applications
Digital objects as "transducers" in scientific web publishing
No full textScientific web publishing offers an attractive bundle of phenomena for feminist technoscientific investigation. This article focuses on research articles in scientific journals and aims at identifying a range of exclusionary practices in the current publishing system, which need to be critically addressed. For this purpose, the functionalities of digital objects are studied using the analogy of a piezoelectric crystal as a transducer in obstetric ultrasonography (Karen Barad 2001). This is embedded in the idea that scholarly communication, and publishing in particular, is characterized by an economy based on gift-giving-for-recognition
Semiometrics: producing a compositional view of influence
No full textHigh-impact academic papers are not necessarily the most cited. For example, Einstein's 'Special Relativity' paper from 1905 received (and continues to receive) fewer citations from other papers than his 'Brownian Motion" paper of the same year, despite the former radically changing the course of an entire scientific discipline to a much greater extent. Similarly, 'impact' metrics using citation count alone are, it is argued, not adequate for determining the scientific influence of papers, authors or small groups of authors. Although valid, they remain controversial when used to determine influence of larger groups or journals. While the term 'impact' has become closely linked to a journal's citation-based Journal Impact Factor score, this thesis uses the term 'influence' to describe the wider effectiveness of research, combining citation and metadata analysis to allow richer calculations to be performed over large-scale document networks. As a result, more qualitative influence ratings can be determined and a broader outlook on scientific disciplines can be produced. These ratings are best applied using an ontology-based data source, allowing more efficient inference than under a traditional RDBMS system, and allowing easier integration between heterogeneous data sources. These metrics, termed 'Semantic Bibliometrics' or 'Semiometrics', can be applied at a variety of levels of granularity, allowing a compositional framework for impact and influence analysis. This thesis describes the process of data preparation, systems architecture, metric value and data integration for such a system, introducing novel approaches at all four stages, thereby creating a working semiometrics system for determining influence at different semantic levels of granularity
Semantic Web Technologies for Digital Libraries: From Libraries to Social Semantic Digital Libraries (SSDL), Over Semantic Digital Libraries (SDL)
No full textDigital libraries have been an important source of information throughout the history of mankind. It has been present in our societies in different forms. Notably, traditional libraries have found their on the desktops of internet users. They have taken the shape of semantic digital libraries, which are accessible at any time, and accordingly provide a more meaningful search. This paper further discusses social semantic digital libraries that also incorporate the social and collaborative aspect
Open access self-archiving: An author study
No full textThis, our second author international, cross-disciplinary study on open access had 1296 respondents. Its focus was on self-archiving. Almost half (49%) of the respondent population have self-archived at least one article during the last three years. Use of institutional repositories for this purpose has doubled and usage has increased by almost 60% for subject-based repositories. Self-archiving activity is greatest amongst those who publish the largest number of papers. There is still a substantial proportion of authors unaware of the possibility of providing open access to their work by self-archiving. Of the authors who have not yet self-archived any articles, 71% remain unaware of the option. With 49% of the author population having self-archived in some way, this means that 36% of the total author population (71% of the remaining 51%), has not yet been appraised of this way of providing open access. Authors have frequently expressed reluctance to self-archive because of the perceived time required and possible technical difficulties in carrying out this activity, yet findings here show that only 20% of authors found some degree of difficulty with the first act of depositing an article in a repository, and that this dropped to 9% for subsequent deposits. Another author worry is about infringing agreed copyright agreements with publishers, yet only 10% of authors currently know of the SHERPA/RoMEO list of publisher permissions policies with respect to self-archiving, where clear guidance as to what a publisher permits is provided. Where it is not known if permission is required, however, authors are not seeking it and are self-archiving without it. Communicating their results to peers remains the primary reason for scholars publishing their work; in other words,
researchers publish to have an impact on their field. The vast majority of authors (81%) would willingly comply with a mandate from their employer or research funder to deposit copies of their articles in an institutional or subject-based repository. A further 13% would comply reluctantly; 5% would not comply with such a mandate
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