COCOON CORE: CO-author REcommendations based on betweenness centrality and interest similarity



Publication Details

Sie, R. L.L., van Engelen, B. Jan., Bitter-Rijpkema, M. & Sloep, P. B. (2014). COCOON CORE: CO-author REcommendations based on betweenness centrality and interest similarity. In N. Manouselis, H. Drachsler, K. Verbert & O. C. Santos (Eds.), Recommender Systems for Technology Enhanced Learning: Research Trends and Applications (pp. 267-282). New York, United States: Springer.


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.

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