Paper Info
Title
Ranking Vicarious Learners in Research Collaboration Networks
Abstract
Despite being a topic of growing interest in social learning theory, vicarious learning has not been well-studied so far in digital library related tasks. In this paper, we address a novel ranking problem in research collaboration networks, which focuses on the role of vicarious learner. We introduce a topology-driven vicarious learning definition and propose the first centrality method for ranking vicarious learners. Results obtained on DBLP networks support the significance and uniqueness of the proposed approach.
Year
DOI
Venue
2013
10.1007/978-3-319-03599-4_11
ICADL
Field
DocType
Citations 
Data science,Social learning theory,Observational learning,Ranking,Computer science,Centrality,Artificial intelligence,Digital library
Conference
2
PageRank 
References 
Authors
0.37
16
2
Name
Order
Citations
PageRank
Andrea Tagarelli147552.29
Roberto Interdonato27012.42