Hyung Jun Ahn
- Information Systems top 1%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Sociology and Political Science top 10%
- Management Information Systems top 5%
- Co-authors
- Sung Joo ParkHong Joo LeeJong Woo KimHabin LeeJusang LeeGottfried VossenPaul ChilderhouseSeung‐Kyu Rhee
- Topics
- Digital Marketing and Social Media (11 papers)Technology Adoption and User Behaviour (7 papers)Recommender Systems and Techniques (6 papers)
- Partner nations
- South KoreaNew ZealandUnited States
In The Last Decade
Hyung Jun Ahn
35 papers receiving 994 citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Information Systems 595
- Computer Vision and Pattern Recognition 235
- Artificial Intelligence 224
- Sociology and Political Science 205
- Management Information Systems 187
Countries citing papers authored by Hyung Jun Ahn
This map shows the geographic impact of Hyung Jun Ahn'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 Hyung Jun Ahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyung Jun Ahn more than expected).
Fields of papers citing papers by Hyung Jun Ahn
This network shows the impact of papers produced by Hyung Jun Ahn. 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 Hyung Jun Ahn. The network helps show where Hyung Jun Ahn may publish in the future.
Co-authorship network of co-authors of Hyung Jun Ahn
This figure shows the co-authorship network connecting the top 25 collaborators of Hyung Jun Ahn. A scholar is included among the top collaborators of Hyung Jun Ahn 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 Hyung Jun Ahn. Hyung Jun Ahn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 28 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 68 | |
| 9 | How does customer's product expertise moderate the usefulness of information recommendation agents in online stores? | 3 |
| 10 | An Exploration of the Impact of Information Privacy Invasion | 9 |
| 11 | 18 | |
| 12 | 20 | |
| 13 | A hybrid collaborative filtering recommender system using a new similarity measure | 2 |
| 14 | 58 | |
| 15 | 69 | |
| 16 | 3 | |
| 17 | 25 | |
| 18 | 5 | |
| 19 | Handshaking Mechanism for Conversation Policy Agreements in Dynamic Agent Environment | 5 |
| 20 | 7 |
About Hyung Jun Ahn
Hyung Jun Ahn is a scholar working on Information Systems and Management, Management Information Systems and Marketing, having authored 44 papers that have together received 1.1k indexed citations. Recurring topics across this work include Digital Marketing and Social Media (11 papers), Technology Adoption and User Behaviour (7 papers) and Recommender Systems and Techniques (6 papers). The work is most often cited by research in Information Systems (595 citations), Management Information Systems (187 citations) and Information Systems and Management (111 citations). Hyung Jun Ahn has collaborated with scholars based in South Korea, New Zealand and United States. Frequent co-authors include Sung Joo Park, Hong Joo Lee, Jong Woo Kim, Habin Lee, Jusang Lee, Gottfried Vossen, Paul Childerhouse, Seung‐Kyu Rhee, Chul Woo Yoo and Se Won Suh. Their work appears in journals such as Construction and Building Materials, Expert Systems with Applications and IEEE Access.
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.