Yiye Ruan
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Advanced Text Analysis Techniques
Papers in
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- Complex Network Analysis Techniques 7
- Opinion Dynamics and Social Influence 2
- Co-authors
- Srinivasan Parthasarathy (8 shared papers)Venu Satuluri (1 shared paper)Amol Ghoting (2 shared papers)Amit Sheth (3 shared papers)Hemant Purohit (3 shared papers)David Fuhry (2 shared papers)Oliver Brdiczka (1 shared paper)Jianqiang Shen (1 shared paper)
- Journals
- Computers in Human Behavior (1 paper)IEEE Data(base) Engineering Bulletin (1 paper)Journal of Bioresource Management (2 papers)Proceedings of the International AAAI Conference on Web and Social Media (1 paper)
- Partner nations
- United States
In The Last Decade
Yiye Ruan
9 papers receiving 212 citations
Peers
Comparison fields: 5 of 44
- Statistical and Nonlinear Physics 130
- Artificial Intelligence 109
- Communication 22
- Information Systems 57
- Computer Vision and Pattern Recognition 43
Countries citing papers authored by Yiye Ruan
This map shows the geographic impact of Yiye Ruan'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 Yiye Ruan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yiye Ruan more than expected).
Fields of papers citing papers by Yiye Ruan
This network shows the impact of papers produced by Yiye Ruan. 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 Yiye Ruan. The network helps show where Yiye Ruan may publish in the future.
Co-authors
The 11 scholars most cited alongside Yiye Ruan, 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 | 2011 | 107 | |
| 2 | 2012 | 40 | |
| 3 | Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter | 2011 | 16 |
| 4 | 2014 | 15 | |
| 5 | 2013 | 15 | |
| 6 | 2014 | 13 | |
| 7 | Prediction of Topic Volume on Twitter | 2012 | 8 |
| 8 | 2014 | 4 | |
| 9 | Summarization via Pattern Utility and Ranking: A Novel Framework for Social Media Data Analytics. | 2013 | 2 |
About Yiye Ruan
Yiye Ruan is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Information Systems, Artificial Intelligence and Communication, having authored 9 papers that have together received 220 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Web Data Mining and Analysis (2 papers), Data Management and Algorithms (2 papers), Advanced Graph Neural Networks (2 papers), Social Media and Politics (2 papers), Opinion Dynamics and Social Influence (2 papers), Spam and Phishing Detection (1 paper) and Sentiment Analysis and Opinion Mining (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (130 citations), Artificial Intelligence (109 citations), Communication (22 citations), Information Systems (57 citations) and Computer Vision and Pattern Recognition (43 citations). Yiye Ruan has collaborated with scholars based in United States. Frequent co-authors include Srinivasan Parthasarathy, Venu Satuluri, Amol Ghoting, Amit Sheth, Hemant Purohit, David Fuhry, Oliver Brdiczka, Jianqiang Shen, Amruta Joshi and Tao Shi. Their work appears in journals such as Computers in Human Behavior, IEEE Data(base) Engineering Bulletin, Journal of Bioresource Management 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.