Chi Wang

1.6k citations
26 papers · 1.2k · 1 hit paper · h-index 13

Impact in

Papers in

Chi Wang

24 papers receiving 1.1k citations

Chi Wang's Hit Papers

Social influence analysis in large-scale networks 2009 · 709 citations
7090+5+11Years since publication200400600

Peers

Chi Wang
Comparison fields: 5 of 121
  • Statistical and Nonlinear Physics 535
  • Process Chemistry and Technology 45
  • Artificial Intelligence 500
  • Information Systems 254
  • Communication 74
Replace Karthik Subbian with:
Karthik Subbian United States
Masashi Toyoda Japan
Kuldeep Singh India
Shashank Sheshar Singh India
Andreas Lommatzsch Germany
Pankaj Gupta United States
Dónal Doyle Ireland
Junjie Wu China
Amitabha Bagchi India
Chi Wang relative to Karthik Subbian United States Karthik Subbian's profile →
Citations per field
00.5×1.6×
Karthik Subbian · 1×
Citations per year

Countries citing papers authored by Chi Wang

Since Specialization
Citations

This map shows the geographic impact of Chi Wang'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 Chi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chi Wang more than expected).

Fields of papers citing papers by Chi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chi Wang. 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 Chi Wang. The network helps show where Chi Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Chi Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chi Wang Line = papers co-authored together Chi Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Social influence analysis in large-scale networks
Hit paper breakdown →
2009709
2
Pervasive and Mobile Computing
201561
3 201660
4 200358
5 201637
6 201537
7 200936
8 199133
9 202123
10 201622
11 200419
12 202218
13 201514
14 201411
15 20087
16 20187
17 20126
18 20134
19 20193
20 20232

About Chi Wang

Chi Wang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics, Signal Processing and Information Systems, having authored 26 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (6 papers), Complex Network Analysis Techniques (5 papers), Advanced Database Systems and Queries (4 papers), Data Management and Algorithms (4 papers), Privacy-Preserving Technologies in Data (3 papers), Caching and Content Delivery (2 papers), Cryptography and Data Security (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (535 citations), Process Chemistry and Technology (45 citations), Artificial Intelligence (500 citations), Information Systems (254 citations) and Communication (74 citations). Chi Wang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Jimeng Sun, Jie Tang, Zi Yang, Adrian Williams, Kaushik Chakrabarti, Surajit Chaudhuri, Bolin Ding, Silu Huang, Kwame-Lante Wright and Zhiqiang Wang. Their work appears in journals such as Atmospheric Environment, Nano Letters, Analytica Chimica Acta, IEEE Transactions on Knowledge and Data Engineering and Talanta.

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.

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