Collaboration and Productivity: an investigation into ‘Scientometrics’ journal and ‘UHasselt’ repository

Egghe, Leo; Goovaerts, Marc; Kretschmer, Hildrun

doi:10.1080/09737766.2008.10700843

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…This finding is reasonable, as this journal is as a major and an old source in the field of iMetrics. This is why most researchers in this field are interested in analysing papers published in Scientometrics (Chen et al, 2012;Ding et al, 2013;Dutt et al, 2003;Egghe et al, 2007;Erfanmanesh et al, 2012;Hou et al, 2008). Despite the fact that the Journal of Informetrics was published later, it belongs to the highly cited ones.…”

Section: Discussionmentioning

confidence: 99%

An author co-citation analysis of 37 years of iMetrics

Khasseh

Soheili

Chelak

2018

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Purpose This research aims to examine the intellectual structure of iMetrics through author co-citation analysis. Design/methodology/approach This research uses common techniques in bibliometrics and social network analysis. It analyses 5,944 records from the Web of Science in the field of iMetrics that are published between 1978 and 2014. Findings Findings indicated that researchers including “Garfield”, “Egghe”, “Glanzel”, “Leydesdorff” and “Price” have received many co-citations. The author co-citation analysis in iMetrics resulted in eight thematic clusters, including “theoretical foundations and citation analysis”, “sociology of science”, “science mapping and visualization”, “network analysis”, “classic laws of bibliometrics”, “webometrics”, “technometrics” and “miscellaneous”. “Theoretical foundations and citation analysis” is the biggest cluster which comprises 59 authors. The results suggest the crucial role of price medallists in shaping the intellectual structure of knowledge in iMetrics. Originality/value Extracting the patterns embedded in the knowledge structure of iMetrics studies provides beneficial information for both researchers and policymakers. This research study is valuable that used an appropriate set of records regarding both recall and precision. Furthermore, this study helps us better understand the characteristics of iMetrics, its subject areas, and the prominent authors in those areas.

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Section: Discussionmentioning

confidence: 99%

An author co-citation analysis of 37 years of iMetrics

Khasseh

Soheili

Chelak

2018

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“…Here, we systematically surveyed how personal gain can be optimized by balancing contradicting motivations accompanying the establishment of collaborative interactions. The repeatedly observed correlation [ 2 , 9 , 32 ] between the personal tendency of researchers to collaborate and the resulting scientific impact points at collaborative interactions as a beneficial professional pattern. Our results demonstrated that across different organization levels and disciplines within the biological sciences there is a remarkably low tendency to collaborate with other entities that are either too much or too little alike.…”

Section: Discussionmentioning

confidence: 99%

The Interplay between Scientific Overlap and Cooperation and the Resulting Gain in Co-Authorship Interactions

Mayrose

Freilich

2015

PLoS ONE

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Considering the importance of scientific interactions, understanding the principles that govern fruitful scientific research is crucial to policy makers and scientists alike. The outcome of an interaction is to a large extent dependent on the balancing of contradicting motivations accompanying the establishment of collaborations. Here, we assembled a dataset of nearly 20,000 publications authored by researchers affiliated with ten top universities. Based on this data collection, we estimated the extent of different interaction types between pairwise combinations of researchers. We explored the interplay between the overlap in scientific interests and the tendency to collaborate, and associated these estimates with measures of scientific quality and social accessibility aiming at studying the typical resulting gain of different interaction patterns. Our results show that scientists tend to collaborate more often with colleagues with whom they share moderate to high levels of mutual interests and knowledge while cooperative tendency declines at higher levels of research-interest overlap, suggesting fierce competition, and at the lower levels, suggesting communication gaps. Whereas the relative number of alliances dramatically differs across a gradient of research overlap, the scientific impact of the resulting articles remains similar. When considering social accessibility, we find that though collaborations between remote researchers are relatively rare, their quality is significantly higher than studies produced by close-circle scientists. Since current collaboration patterns do not necessarily overlap with gaining optimal scientific quality, these findings should encourage scientists to reconsider current collaboration strategies.

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“…They have emphasized different aspects of scientific collaboration, including (a) the cognitive/disciplinary factor; for example, the emerging interdisciplinary areas that require collaboration, and so on (Beaver, 2001;Katz & Martin, 1997;Hara, Solomon, Kim, & Sonnenwald, 2003); (b) the geographic factor; for example, researchers who are geographically closer are more likely to collaborate (Katz, 1994;Luukkonen et al, 1992;Schubert & Braun, 1990); (c) the organizational factor; for example, leadership and management of scientific collaboration also play a noticeable role (Finholt & Olson, 1997); (d) the political factor; for example, governments are keen to encourage the level of participation in scientific collaboration (Clarke, 1967;Smith, 1958); (e) the socioeconomic factor (Maglaughlin & Sonnenwald, 2005); (f) resource accessibility (Cohen, 2000); and (g) social networks and personal factors; prestige and productivity of researchers also impact their participation in scientific collaboration (Egghe, Goovaerts, & Kretschmer, 2008;Glänzel, 2000;Glänzel & Schubert, 2001). However, most of the previous studies have either analyzed various possible factors theoretically and qualitatively or verified only an individual factor with quantitative evidences.…”

Section: Related Workmentioning

confidence: 98%

Mining enriched contextual information of scientific collaboration: A meso perspective

Ding

2011

J. Am. Soc. Inf. Sci.

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Collaboration and Productivity: an investigation into ‘Scientometrics’ journal and ‘UHasselt’ repository

Cited by 9 publications

References 9 publications

An author co-citation analysis of 37 years of iMetrics

An author co-citation analysis of 37 years of iMetrics

The Interplay between Scientific Overlap and Cooperation and the Resulting Gain in Co-Authorship Interactions

Mining enriched contextual information of scientific collaboration: A meso perspective

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