Author ORCID Identifier
Document Type
Conference Proceeding
Publication Date
4-11-2016
Publication Title
WWW Companion: Proceedings of the 25th International Conference Companion on World Wide Web
Volume
April 2016
First Page
375
Last Page
380
Abstract
Academic publication is a key indicator for measuring scholars' scientific productivity and has a crucial impact on their future career. Previous work has identified the positive association between the number of collaborators and academic productivity, which motivates the problem of tracing and predicting potential collaborators for junior scholars. Nevertheless, the insufficient publication record makes current approaches less effective for junior scholars. In this paper, we present an exploratory study of predicting junior scholars' future co-authorship in three different network density. By combining features based on affiliation, geographic and content information, the proposed model significantly outperforms the baseline methods by 12% in terms of sensitivity. Furthermore, the experiment result shows the association between network density and feature selection strategy. Our study sheds light on the re-evaluation of existing approaches to connect scholars in the emerging worldwide Web of Scholars.
Recommended Citation
Tsai, Chun-Hua and Lin, Yuru, "Tracing and Predicting Collaboration for Junior Scholars" (2016). Information Systems and Quantitative Analysis Faculty Publications. 149.
https://digitalcommons.unomaha.edu/isqafacpub/149
Comments
© {Authors | ACM} {2016}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in {WWW Companion: Proceedings of the 25th International Conference Companion on World Wide Web}, https://doi.org/10.1145/2872518.2890516