Ranran Wang

701 citations
35 papers · 502 · h-index 11

Impact in

Papers in

Ranran Wang

27 papers receiving 487 citations

Peers

Ranran Wang
Comparison fields: 5 of 112
  • Computer Networks and Communications 129
  • Information Systems 103
  • Artificial Intelligence 125
  • Transportation 24
  • Signal Processing 34
Replace Su Yang with:
Su Yang China
Waleed Albattah Saudi Arabia
Jinpeng Chen China
Ying Cai China
Zaheer Ullah Khan China
You Song China
Mejdl Safran Saudi Arabia
Minghong Liao China
Dariusz Mrozek Poland
Anupam Baliyan India
Ranran Wang relative to Su Yang China Su Yang's profile →
Citations per field
00.5×2.7×
Su Yang · 1×
Citations per year

Countries citing papers authored by Ranran Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ranran Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ranran 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 Ranran Wang Line = papers co-authored together Ranran Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200985
2 201969
3 202066
4 202058
5 201937
6 201936
7 202222
8 201918
9 202214
10 202013
11 202312
12 202310
13 20229
14 20248
15 20218
16 20198
17 20237
18 20244
19 20244
20 20252

About Ranran Wang

Ranran Wang is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics and Sociology and Political Science, having authored 35 papers that have together received 502 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Recommender Systems and Techniques (5 papers), Caching and Content Delivery (5 papers), Spam and Phishing Detection (4 papers), Misinformation and Its Impacts (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Music and Audio Processing (2 papers) and Cooperative Communication and Network Coding (2 papers). The work is most often cited by research in Computer Networks and Communications (129 citations), Information Systems (103 citations), Artificial Intelligence (125 citations), Transportation (24 citations) and Signal Processing (34 citations). Ranran Wang has collaborated with scholars based in China, Japan and Saudi Arabia. Frequent co-authors include Yin Zhang⋆, Xiao Ma, M. Shamim Hossain, Yujie Li, Mohsen Guizani, Huimin Lu, Mohammed F. Alhamid, Chi Jiang, Jianmin Lu and Meikang Qiu. Their work appears in journals such as IEEE Transactions on Services Computing, IEEE Transactions on Intelligent Transportation Systems, IEEE Wireless Communications, Computers and Electronics in Agriculture and IEEE Transactions on Mobile Computing.

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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