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Cross-community <es
• The importance of cross-community <es
– In cita<on networks, cross-community cita<on
paYerns are characteris<c for high impact papers
[Shi. et al., 2010]
– Same holds true in case of cross-community
scien<fic collabora<on [Newman, 2004; LambioYe
and Panzarasa, 2009]](https://image.slidesharecdn.com/wosp2015-151223101817/75/Semantometrics-in-Coauthorship-Networks-Fulltext-based-Approach-for-Analysing-Patterns-of-Research-Collaboration-5-2048.jpg)
Uploaded byDasha Herrmannova
Semantometrics in Coauthorship Networks: Fulltext-based Approach for Analysing Patterns of Research Collaboration
The document explores the use of semantometrics, a set of full-text based metrics, to analyze research collaboration and citation networks, particularly focusing on cross-community ties. It distinguishes between different types of collaborations, such as emerging vs. established and interdisciplinary vs. intradisciplinary, using fulltext analysis to identify these relationships. The findings highlight the importance of fulltext data in understanding scholarly collaboration patterns and their impact on academic publishing.
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Semantometrics in Coauthorship Networks: Fulltext-based Approach for Analysing Patterns of Research Collaboration
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- 6. 6/18 How to iden<fy cross-community <es? • From cita<on/coauthorship network – E.g. betweeness centrality • From fulltext – Seman<c similarity • Different types of collabora<on when wri<ng a paper – Emerging vs. established – Interdisciplinary vs. intradisciplinary – Etc.
- 7. 7/18 Emerging vs. established research collabora<on • Endogamy – In social sciences: the prac<ce or tendency of marrying within a social group – In research: collabora<on within a group of authors – Higher endogamy = more frequent collabora<on endo Ad A a A d a endo p x L p endo x L p p Publica<on A Set of authors d(A) Papers coauthored by authors in A L(p) Set of all subsets with at least two authors of p
- 8. 8/18 Interdisciplinary vs. intradisciplinary research collabora<on • Seman<c distance of publica<on authors – Higher author distance indicates more distant communi<es – Author publica<on record considered as a single text a distp A p A p dist a , a a A p ,a A p ,a a p Publica<on A(p) Set of authors of p
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- 10. 10/18 Experiment • What is the distribu<on of the four different types of collabora<on in scholarly literature? • CORE (core.ac.uk) used as a dataset – Cross-discipline – Enables sampling by authors and ins<tu<ons – Selected sample • Fulltext documents from Open Research Online repository (ORO) • All other fulltext publica<ons of the authors from ORO found in CORE
- 11. 11/18 Dataset sta<s<cs Fulltext ar<cles from ORO 4,207 Number of authors 8,473 Average number of publica<ons per author 7.61 Max number of publica<ons per author 310 Average number of authors per publica<on 4.31 Max number of authors per publica<on 25 Average number of received cita<ons 0.30 Average number of collaborators 80.23 Total number of publica<ons 30,484
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- 17. 17/18 Conclusions • Fulltext necessary • Semantometrics are a new class of methods • We showed one method to recognise types of scholarly collabora<on
- 18. 18/18 References • Xiaolin Shi, Jure Leskovec, and Daniel A Mcfarland (2010) Ci0ng for High Impact • M. E. J. Newman (2004) Coauthorship networks and pa:erns of scien0fic collabora0on • R. LambioYe and P. Panzarasa (2009) Communi0es, knowledge crea0on, and informa0on diffusion