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COCOON CORE: CO-author REcommendations Based on Betweenness Centrality and Interest Similarity

  • Rory L. L. SieEmail author
  • Bart Jan van Engelen
  • Marlies Bitter-Rijpkema
  • Peter B. Sloep

Abstract

When researchers are to write a new article, they often seek co-authors who are knowledgeable on the article’s subject. However, they also strive for acceptance of their article. Based on this otherwise intuitive process, the current article presents the COCOON CORE tool that recommends candidate co-authors based on like-mindedness and power. Like-mindedness ensures that co-authors share a common ground, which is necessary for seamless cooperation. Powerful co-authors foster adoption of an article’s research idea by the community. Two experiments were conducted, one focusing on the perceived quality of the recommendations that COCOON CORE generates and one focusing on the usability of COCOON CORE. Results indicate that participants perceive the recommendations moderately positively. Particularly, they value the recommendations that focus fully on finding influential peers and the recommendation in which they themselves can adjust the balance between finding influential peers and like-minded peers. Also, the usability of COCOON CORE is perceived to be moderately good.

Keywords

Social network analysis Science 2.0 Co-authorship Research network Informetrics Recommender systems Scientometrics 

Notes

Acknowledgments

The authors thank Dr. Lora Aroyo from the VU University Amsterdam for her insightful comments during the design and implementation phases of COCOON CORE.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Rory L. L. Sie
    • 1
    Email author
  • Bart Jan van Engelen
    • 3
  • Marlies Bitter-Rijpkema
    • 2
  • Peter B. Sloep
    • 2
  1. 1.AmsterdamThe Netherlands
  2. 2.Open Universiteit NederlandHeerlenNetherlands
  3. 3.Dandelion Group BVRotterdamNetherlands

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