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.
An empirical study of the factors affecting social network service use
This map shows the geographic impact of Ohbyung Kwon'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 Ohbyung Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ohbyung Kwon more than expected).
This network shows the impact of papers produced by Ohbyung Kwon. 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 Ohbyung Kwon. The network helps show where Ohbyung Kwon may publish in the future.
Co-authorship network of co-authors of Ohbyung Kwon
This figure shows the co-authorship network connecting the top 25 collaborators of Ohbyung Kwon.
A scholar is included among the top collaborators of Ohbyung Kwon 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 Ohbyung Kwon. Ohbyung Kwon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kwon, Ohbyung, et al.. (2017). Financial Fraud Detection using Text Mining Analysis against Municipal Cybercriminality. Journal of Intelligence and Information Systems. 23(3). 119–138.1 indexed citations
10.
Kwon, Ohbyung, et al.. (2014). Factors Affecting Sustainable Web Technology Adoption. 19(4). 205–229.1 indexed citations
Lee, Yonnim & Ohbyung Kwon. (2010). Gender Differences in Continuance Intention of On-line Shopping Services. Asia Pacific Journal of Information Systems. 20(3). 51–72.2 indexed citations
13.
Kwon, Ohbyung. (2009). Context Prediction Using Right and Wrong Patterns to Improve Sequential Matching Performance for More Accurate Dynamic Context-Aware Recommendation. Asia Pacific Journal of Information Systems. 19(3). 51–67.1 indexed citations
14.
Kwon, Ohbyung, et al.. (2009). Association Based Reasoning Method Using Rescorla-Wagner Model and Galton Free Association Test for Augmented Reality E-Commerce. The e-Business Studies. 14(3). 131–151.2 indexed citations
Kwon, Ohbyung, et al.. (2008). A Study of Factors Influencing Ubiquitous Computing Service Acceptance. The e-Business Studies. 13(2). 117–147.15 indexed citations
17.
Kwon, Ohbyung, et al.. (2007). Applying Polite level Estimation and Case-Based Reasoning to Context-Aware Mobile Interface System. Journal of Intelligence and Information Systems. 13(3). 141–160.1 indexed citations
18.
Kwon, Ohbyung, Yixing Wen, & Min-Yong Kim. (2007). Factors Affecting Blog Use : An Empirical Study Using Extended TAM and Perceived Encouragement. The e-Business Studies. 12(4). 165–184.4 indexed citations
19.
Kwon, Ohbyung & Jihoon Kim. (2007). Applying Ubi-SERVQUAL to Assessing the Quality of Ubiquitous Service Scenarios. Journal of the Korean Operations Research and Management Science Society. 32(1). 1–13.1 indexed citations
20.
Kwon, Ohbyung, et al.. (2007). Space Reengineering and Amended UML Approach to Requirement Analysis for Ubiquitous Smart Space Development. The e-Business Studies. 12(4). 99–125.1 indexed citations
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.