Hongchen Wu

422 citations
25 papers · 271 · 1 hit paper · h-index 9

Impact in

Papers in

Hongchen Wu

20 papers receiving 264 citations

Hongchen Wu's Hit Papers

Multimodal fake news detection via progressive fusion networks 2022 · 134 citations
1340+1+2Years since publication4080120

Peers

Hongchen Wu
Comparison fields: 5 of 60
  • Information Systems 140
  • Sociology and Political Science 167
  • Artificial Intelligence 120
  • Signal Processing 32
  • Statistical and Nonlinear Physics 21
Replace Yuming Lin with:
Yuming Lin China
Yabo Wang China
Pawan Kumar Verma India
Enrico Palumbo Italy
Andreas Lommatzsch Germany
M. Suresha India
Erion Çano Italy
Wu-Jun Li China
Jitao Sang China
Sivaramakrishnan Natarajan United States
Hongchen Wu relative to Yuming Lin China Yuming Lin's profile →
Citations per field
00.5×4.5×
Yuming Lin · 1×
Citations per year

Countries citing papers authored by Hongchen Wu

Since Specialization
Citations

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

Fields of papers citing papers by Hongchen Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multimodal fake news detection via progressive fusion networks
Hit paper breakdown →
2022134
2 202325
3 201917
4 201314
5 201712
6 201912
7 202310
8 201810
9 20189
10 20206
11 20204
12 20163
13 20123
14 20252
15 20212
16 20182
17 20232
18 20232
19 20231
20 20221

About Hongchen Wu

Hongchen Wu is a scholar working on Information Systems, Sociology and Political Science, Artificial Intelligence, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 25 papers that have together received 271 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (9 papers), Spam and Phishing Detection (6 papers), Misinformation and Its Impacts (5 papers), Complex Network Analysis Techniques (4 papers), Topic Modeling (3 papers), Privacy, Security, and Data Protection (3 papers), Privacy-Preserving Technologies in Data (3 papers) and Mobile Crowdsensing and Crowdsourcing (3 papers). The work is most often cited by research in Information Systems (140 citations), Sociology and Political Science (167 citations), Artificial Intelligence (120 citations), Signal Processing (32 citations) and Statistical and Nonlinear Physics (21 citations). Hongchen Wu has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Huaxiang Zhang, Jing Jing, Jie Sun, Xinjun Wang, Lizhen Cui, Hongzhu Yu, Qingzhong Li, Zhaohui Peng, Bing Yu and Kangning Chen. Their work appears in journals such as IEEE Access, Information Processing & Management, Applied Intelligence, Wireless Communications and Mobile Computing and Neurocomputing.

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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