Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Driver injury severity: an application of ordered probit models
2002492 citationsKara M. Kockelman, Young‐Jun KweonAccident Analysis & Preventionprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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Countries citing papers authored by Young‐Jun Kweon
Since
Specialization
Citations
This map shows the geographic impact of Young‐Jun Kweon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Young‐Jun Kweon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young‐Jun Kweon more than expected).
This network shows the impact of papers produced by Young‐Jun Kweon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Young‐Jun Kweon. The network helps show where Young‐Jun Kweon may publish in the future.
Co-authorship network of co-authors of Young‐Jun Kweon
This figure shows the co-authorship network connecting the top 25 collaborators of Young‐Jun Kweon.
A scholar is included among the top collaborators of Young‐Jun Kweon based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Young‐Jun Kweon. Young‐Jun Kweon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kweon, Young‐Jun, et al.. (2014). Drivers’ Lane-Changing Behavior at Bus Stops on Three-Lane Roadways. Transportation Research Board 93rd Annual MeetingTransportation Research Board.4 indexed citations
6.
Kweon, Young‐Jun, et al.. (2013). Investigation of the Safety Effects of Edge and Centerline Markings on Narrow, Low-Volume Roads.2 indexed citations
7.
Kweon, Young‐Jun, et al.. (2013). Identifying High-Crash-Risk Intersections. Transportation Research Record Journal of the Transportation Research Board. 2364(1). 44–50.15 indexed citations
8.
Kweon, Young‐Jun. (2011). What Affects Annual Changes in Traffic Safety Measures in Virginia? A Macroscopic Perspective. Transportation Research Board 90th Annual MeetingTransportation Research Board.3 indexed citations
Kweon, Young‐Jun, et al.. (2010). Appropriate Regression Model Types for Empirical Bayes Method and SafetyAnalyst. Transportation Research Board 89th Annual MeetingTransportation Research Board.2 indexed citations
Kim, Kwang Sik, et al.. (2009). Effective Administrative Sanction for Traffic Violation: License Suspension or Revocation. Transportation Research Board 88th Annual MeetingTransportation Research Board.
Kweon, Young‐Jun. (2007). Development of a Safety Evaluation Procedure for Identifying High-Risk Signalized Intersections in the Virginia Department of Transportation’sNorthern Virginia District.1 indexed citations
Kweon, Young‐Jun & Kara M. Kockelman. (2005). Safety Effects of Speed Limit Changes. Transportation Research Record Journal of the Transportation Research Board. 1908(1). 148–158.25 indexed citations
18.
Kweon, Young‐Jun, et al.. (2004). NONPARAMETRIC REGRESSION ESTIMATION OF HOUSEHOLD VMT.6 indexed citations
Kockelman, Kara M. & Young‐Jun Kweon. (2002). Driver injury severity: an application of ordered probit models. Accident Analysis & Prevention. 34(3). 313–321.492 indexed citations breakdown →
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.