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most obvious scientometric example, “joint action” means joint authorship, i.e., an author is said to have a co-author partnership ability φ, if with φ of his/her n co-authors had at least φ joint papers each, and with the other ( n − φ) co-authors

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in nano science and engineering. We also study the structure of citation network of the papers authored by these scientists. The co-author network is a type of social network and the paper citation network is a type of information science network

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Structuring scientific activities by co-author analysis

An expercise on a university faculty level

Scientometrics
Authors:
H. Peters
and
A. Van Raan

Abstract  

In this paper we apply co-author analysis to create from a large set of publications clusters of collaborating researchers within a faculty of chemical engineering. Results have been discussed with an expert. The co-author clusters appeared to be meaningful, with respect to the identification of research groups, the relations within these groups, as well as to relations between these groups and changes in time. Also differences between ISI-based and non-ISI based maps proved to be consistent with the expert's opinion. Many clusters represent collaborating authors grouped around a full professor, mostly the department chairman. Co-author analysis can be used, for example, as an important tool in evaluative bibliometrics in order to make a first identification of research groups in unknown universities or organizations.

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Policy” ( EC 2007 ). This paper aims at understanding which membership status (inside or outside the EU, though still inside ERA) has been a better condition when it comes to talk about the extent to which international co-authored publications are signed

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problem and let all co-authors take full credit. Bad incentives are the result: Authors may add each other to their papers even without a contribution. 1 The second solution—“egalitarian weights”—is to share the credit equally between the co-authors

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The paper presents the results of a comprehensive study on Anna Dostoevskaja’s role in the creative process of Fyodor Dostoevsky. She was not only the wife of the great writer but a professional shorthand writer and a copyist as well. At the time of writing his novel The Gambler, Dostoevsky and his assistant worked out a model of creativity in which priority was given to stenographic writing that could trace and fix the writer’s exciting ideas. During the subsequent work on his literary writings including e.g. The Great Pentateuch, this model of the creative process remained unaltered. Dostoevsky’s wife was his Muse, co-thinker, interlocutor, the first listener and the first critic of his creations, and the co-author of burlesque verses. Her impressions, stories, and their private conversations were used by Dostoevsky in his literary works. Several years of joint creative work with the brilliant writer developed in his assistant literary skills thanks to which she wrote masterful memoirs that obtained worldwide recognition. Dostoevsky appreciated his wife’s contribution to his literary activity thereby dedicating his greatest novel The Brothers Karamazov to her.

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Summary  

Large scale bibliometric analysis is often hindered by the presence of homonyms, or namesakes, of the researchers of interest in literature databases. This makes it difficult to build up a true picture of a researcher's publication record, as publications by another researcher with the same name will be included in search results. Using additional information such as title and author addresses, an expert in the field can generally tell if a paper is by a researcher or a namesake; however, manual checking is not practical in large scale studies. Previously various methods have been used to address this problem, chiefly based on filtering by subject, funding acknowledgement or author address. Co-author inclusion is a novel algorithmic method based on co-authorship for dealing with problems of homonyms in large bibliometric surveys. We compared co-author inclusion and subject and funding based filter against the manual assignment of papers by a subject expert (which we assumed to be correct). The subject and funding based filtering identifies only 75% as many papers as assigned by manual scoring. By using co-author inclusion once we increase this to 95%, two further rounds produces 99% as many papers as manual filtering. Although the number of papers identified that were not assigned to the PIs manually also increases, the absolute number is low: rising from 0.2% papers with subject and funding filtering, to 3% papers for three rounds of co-author inclusion.

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-degree. Schubert ( 2012 ) notes that φ is equal to one if—in a co-authorship network—the author has an arbitrary number of double-authored papers with the same co-author; or if the author has an arbitrary number of co-authored papers with no co-author occurring

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Abstract  

Although many studies have analyzed the “synchronic” correlation of properties between authors and their co-authors, the “diachronic” correlation of properties, i.e., the correlation between their subsequent and precedent activity, has not yet been sufficiently studied using quantitative methods. This study pays attention not only to productivity but also the importance in the collaboration network as a measure of the researcher’s activity, and clarifies whether there is any connection between (i) the researcher’s activity subsequent to a collaboration and (ii) the collaborator’s precedent activity, aiming at deriving knowledge about the diachronic effect of collaborators.

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-enhancing). (4) A reference to my book on the topic (self-enhancement and to encourage sales). (5) A reference to an earlier work I had conducted on this topic (informative and self-enhancing). (6) A co-authored paper with two other colleagues to show research

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