Title
Academic Influence Aware and Multidimensional Network Analysis for Research Collaboration Navigation Based on Scholarly Big Data
Abstract
Scholarly big data, which is a large-scale collection of academic information, technical data, and collaboration relationships, has attracted increasing attentions, ranging from industries to academic communities. The widespread adoption of social computing paradigm has made it easier for researchers to join collaborative research activities and share academic data more extensively than ever before across the highly interlaced academic networks. In this study, we focus on the academic influence aware and multidimensional network analysis based on the integration of multi-source scholarly big data. Following three basic relations: Researcher-Researcher, Researcher-Article, and Article-Article, a set of measures is introduced and defined to quantify correlations in terms of activity-based collaboration relationship, specialty-aware connection, and topic-aware citation fitness among a series of academic entities (e.g., researchers and articles) within a constructed multidimensional network model. An improved Random Walk with Restart (RWR) based algorithm is developed, in which the time-varying academic influence is newly defined and measured in a certain social context, to provide researchers with research collaboration navigation for their future works. Experiments and evaluations are conducted to demonstrate the practicability and usefulness of our proposed method in scholarly big data analysis using DBLP and ResearchGate data.
Year
DOI
Venue
2021
10.1109/TETC.2018.2860051
IEEE Transactions on Emerging Topics in Computing
Keywords
DocType
Volume
Multidimensional network analysis,academic influence,scholarly big data,scholarly recommendation,research collaboration
Journal
9
Issue
ISSN
Citations 
1
2168-6750
10
PageRank 
References 
Authors
0.48
0
5
Name
Order
Citations
PageRank
Xiaokang Zhou122525.50
Wei Liang2676.75
Kevin I-Kai Wang316729.65
Runhe Huang440756.46
Jin, Q.523333.40