Junting Ye
Impact in
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- scientometrics and bibliometrics research
- General Social Sciences top 5%
- Computational and Text Analysis Methods
Papers in
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- Spam and Phishing Detection 2
- Web Data Mining and Analysis 1
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- Data Quality and Management 3
- Co-authors
- Leman Akoglu (3 shared papers)Steven Skiena (4 shared papers)Qinghua Zheng (4 shared papers)Vivek Kulkarni (1 shared paper)William Yang Wang (1 shared paper)Tetsuya Sakai (2 shared papers)Yifan Hu (1 shared paper)Barış Coşkun (1 shared paper)
- Journals
- Information Retrieval (1 paper)Lecture notes in computer science (3 papers)Journal of Networks (1 paper)Proceedings of the ... ACM International Conference on Information & Knowledge Management (1 paper)Conference on Empirical Methods in Natural Language Processing (EMNLP) (1 paper)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Junting Ye
11 papers receiving 274 citations
Peers
Comparison fields: 5 of 37
- Statistics, Probability and Uncertainty 43
- General Social Sciences 18
- Information Systems 109
- Artificial Intelligence 76
- Management Science and Operations Research 36
Countries citing papers authored by Junting Ye
This map shows the geographic impact of Junting Ye'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 Junting Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junting Ye more than expected).
Fields of papers citing papers by Junting Ye
This network shows the impact of papers produced by Junting Ye. 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 Junting Ye. The network helps show where Junting Ye may publish in the future.
Co-authors
The 14 scholars most cited alongside Junting Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 74 | |
| 2 | 2017 | 62 | |
| 3 | 2018 | 48 | |
| 4 | 2015 | 39 | |
| 5 | 2013 | 15 | |
| 6 | 2021 | 15 | |
| 7 | 2019 | 14 | |
| 8 | 2019 | 14 | |
| 9 | 2018 | 3 | |
| 10 | 2012 | 2 | |
| 11 | 2014 | 1 |
About Junting Ye
Junting Ye is a scholar working on Information Systems, Management Science and Operations Research, Artificial Intelligence, General Social Sciences and Statistics, Probability and Uncertainty, having authored 11 papers that have together received 287 indexed citations. Recurring topics across this work include Data Quality and Management (3 papers), Topic Modeling (3 papers), Spam and Phishing Detection (2 papers), Authorship Attribution and Profiling (2 papers), Semantic Web and Ontologies (1 paper), Sentiment Analysis and Opinion Mining (1 paper), Misinformation and Its Impacts (1 paper) and Web Data Mining and Analysis (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (43 citations), General Social Sciences (18 citations), Information Systems (109 citations), Artificial Intelligence (76 citations) and Management Science and Operations Research (36 citations). Junting Ye has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Leman Akoglu, Steven Skiena, Qinghua Zheng, Vivek Kulkarni, William Yang Wang, Tetsuya Sakai, Yifan Hu, Barış Coşkun, Meizhu Liu and Hong Qin. Their work appears in journals such as Information Retrieval, Lecture notes in computer science, Journal of Networks, Proceedings of the ... ACM International Conference on Information & Knowledge Management and Conference on Empirical Methods in Natural Language Processing (EMNLP).
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.