Junting Ye
Impact in
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Hate Speech and Cyberbullying Detection
- Information Systems top 10%
- Spam and Phishing Detection
Papers in
-
- Topic Modeling 3
- Semantic Web and Ontologies 1
-
- Misinformation and Its Impacts 2
- Media Influence and Politics 2
- Co-authors
- Leman Akoglu (2 shared papers)Steven Skiena (2 shared papers)Steve Skiena (1 shared paper)Vivek Kulkarni (1 shared paper)William Yang Wang (1 shared paper)Qinghua Zheng (3 shared papers)Tetsuya Sakai (2 shared papers)Jun Liu (1 shared paper)
- Journals
- Patient Preference and Adherence (1 paper)Information Retrieval (1 paper)Journal of Networks (1 paper)Proceedings of the International AAAI Conference on Web and Social Media (1 paper)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Junting Ye
9 papers receiving 169 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 118
- Information Systems 81
- General Social Sciences 9
- Management Science and Operations Research 30
- Family Practice 4
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 16 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 | 55 | |
| 2 | 2018 | 41 | |
| 3 | 2015 | 31 | |
| 4 | 2019 | 12 | |
| 5 | 2019 | 12 | |
| 6 | 2013 | 10 | |
| 7 | 2021 | 10 | |
| 8 | 2018 | 6 | |
| 9 | 2014 | 1 |
About Junting Ye
Junting Ye is a scholar working on Artificial Intelligence, Sociology and Political Science, Information Systems, Computer Networks and Communications and Management Science and Operations Research, having authored 9 papers that have together received 178 indexed citations. Recurring topics across this work include Spam and Phishing Detection (3 papers), Topic Modeling (3 papers), Misinformation and Its Impacts (2 papers), Media Influence and Politics (2 papers), Data Quality and Management (2 papers), Network Security and Intrusion Detection (2 papers), Semantic Web and Ontologies (1 paper) and Data Management and Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (118 citations), Information Systems (81 citations), General Social Sciences (9 citations), Management Science and Operations Research (30 citations) and Family Practice (4 citations). Junting Ye has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Leman Akoglu, Steven Skiena, Steve Skiena, Vivek Kulkarni, William Yang Wang, Qinghua Zheng, Tetsuya Sakai, Jun Liu, Cong Li and Xiangrong Ye. Their work appears in journals such as Patient Preference and Adherence, Information Retrieval, Journal of Networks and Proceedings of the International AAAI Conference on Web and Social Media.
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.