To whom and why should I connect? Co-author recommendation based on powerful and similar peers Online publication date: Wed, 31-Dec-2014
by Rory L.L. Sie; Hendrik Drachsler; Marlies Bitter-Rijpkema; Peter Sloep
International Journal of Technology Enhanced Learning (IJTEL), Vol. 4, No. 1/2, 2012
Abstract: The present paper offers preliminary outcomes of a user study that investigated the acceptance of a recommender system that suggests future co-authors for scientific article writing. The recommendation approach is twofold: network information (betweenness centrality) and author (keyword) similarity are used to compute the utility of peers in a network of co-authors. Two sets of recommendations were provided to the participants: Set one focused on all candidate authors, including co-authors of a target user to strengthen current bonds and strive for acceptance of a certain research topic. Set two focused on solely new co-authors of a target user to foster creativity, excluding current co-authors. A small-scale evaluation suggests that the utility-based recommendation approach is promising, but to maximise outcome, we need to (a) compensate for researchers' interests that change over time and (b) account for multi-person co-authored papers.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Technology Enhanced Learning (IJTEL):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com