Paper Info
Title
Visualizing Research Impact through Citation Data.
Abstract
Research impact plays a critical role in evaluating the research quality and influence of a scholar, a journal, or a conference. Many researchers have attempted to quantify research impact by introducing different types of metrics based on citation data, such as h-index, citation count, and impact factor. These metrics are widely used in the academic community. However, quantitative metrics are highly aggregated in most cases and sometimes biased, which probably results in the loss of impact details that are important for comprehensively understanding research impact. For example, which research area does a researcher have great research impact on? How does the research impact change over time? How do the collaborators take effect on the research impact of an individual? Simple quantitative metrics can hardly help answer such kind of questions, since more detailed exploration of the citation data is needed. Previous work on visualizing citation data usually only shows limited aspects of research impact and may suffer from other problems including visual clutter and scalability issues. To fill this gap, we propose an interactive visualization tool, ImpactVis, for better exploration of research impact through citation data. Case studies and in-depth expert interviews are conducted to demonstrate the effectiveness of ImpactVis.
Year
DOI
Venue
2018
10.1145/3132744
TiiS
Keywords
Field
DocType
Research impact, publication and citation, visualization
Data science,Visual clutter,Computer science,Visualization,Citation,Interactive visualization,Academic community,Scalability,Impact factor,Distributed computing
Journal
Volume
Issue
ISSN
8
1
2160-6455
Citations 
PageRank 
References 
3
0.37
26
Authors
5
Name
Order
Citations
PageRank
Yong Wang19114.27
Conglei Shi233512.95
Liangyue Li313710.68
Hanghang Tong43560202.37
Huamin Qu52033115.33