Shanchan Wu
- Artificial Intelligence top 5%
- Advanced Text Analysis Techniques 5
- Topic Modeling 4
- Information Systems top 10%
- Web Data Mining and Analysis 5
- Recommender Systems and Techniques 2
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- Open Education and E-Learning 3
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- Complex Network Analysis Techniques 11
- Opinion Dynamics and Social Influence 4
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- Digital Marketing and Social Media 2
- Journals
- Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)KTH Publication Database DiVA (KTH Royal Institute of Technology) (2 papers)Proceedings of the International AAAI Conference on Web and Social Media (1 paper)
- Partner nations
- United StatesSwedenSaudi Arabia
In The Last Decade
Shanchan Wu
18 papers receiving 319 citations
Peers
Comparison fields: 5 of 43
- Artificial Intelligence 265
- Information Systems 75
- Computer Science Applications 13
- Statistical and Nonlinear Physics 26
- Management Science and Operations Research 24
Countries citing papers authored by Shanchan Wu
This map shows the geographic impact of Shanchan Wu'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 Shanchan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shanchan Wu more than expected).
Fields of papers citing papers by Shanchan Wu
This network shows the impact of papers produced by Shanchan Wu. 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 Shanchan Wu. The network helps show where Shanchan Wu may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Shanchan Wu, 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 | 2021 | 1 | |
| 2 | 2019 | 220 | |
| 3 | 2019 | 19 | |
| 4 | 2016 | 2 | |
| 5 | Image Discovery and Insertion for Custom Publishing | 2015 | 4 |
| 6 | 2015 | 15 | |
| 7 | 2015 | 8 | |
| 8 | 2015 | 17 | |
| 9 | 2015 | 21 | |
| 10 | 2014 | 1 | |
| 11 | 2014 | 5 | |
| 12 | Prediction in a Microblog Hybrid Network Using Bonacich Potential | 2013 | 1 |
| 13 | 2012 | 2 | |
| 14 | 2012 | 8 | |
| 15 | 2011 | 2 | |
| 16 | 2011 | 0 | |
| 17 | 2011 | 4 | |
| 18 | 2011 | 2 | |
| 19 | Exploiting social media to provide humanitarian users with event search and recommendations. | 2010 | 4 |
About Shanchan Wu
Shanchan Wu is a scholar working on Statistical and Nonlinear Physics, Computer Science Applications and Information Systems, having authored 19 papers that have together received 336 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (11 papers), Advanced Text Analysis Techniques (5 papers), Web Data Mining and Analysis (5 papers), Topic Modeling (4 papers), Opinion Dynamics and Social Influence (4 papers), Open Education and E-Learning (3 papers), Digital Marketing and Social Media (2 papers) and Recommender Systems and Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (265 citations), Information Systems (75 citations) and Computer Science Applications (13 citations). Shanchan Wu has collaborated with scholars based in United States, Sweden and Saudi Arabia. Frequent co-authors include Yifan He, Jerry Liu, Louiqa Raschid, Jian Fan, Lei Liu, Georgia Koutrika, Kai Fan, Qiong Zhang, William Rand and Henric Johnson. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence, KTH Publication Database DiVA (KTH Royal Institute of Technology) 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.