Ching‐man Au Yeung

1.2k citations
27 papers · 700 indexed · 1 hit paper · h-index 12

Ching‐man Au Yeung

26 papers receiving 663 citations

Hit Papers

“Popularity Effect” in User-Generated Content: Evidence f...20142026201820222014100200300

Peers

Ching‐man Au Yeung
Comparison fields: 5 of 55
  • Artificial Intelligence 306
  • Sociology and Political Science 287
  • Information Systems 243
  • Communication 125
  • Statistical and Nonlinear Physics 115
Replace Elena Zheleva with:
Elena Zheleva United States
Hila Becker United States
Eduarda Mendes Rodrigues United Kingdom
Muhammad Shahid Iqbal Malik Pakistan
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Wanita Sherchan Australia
Don Turnbull United States
Xiaolin Shi United States
Chien Chin Chen Taiwan
Jin‐Cheon Na Singapore
Ching‐man Au Yeung relative to Elena Zheleva United States Elena Zheleva's profile →
Citations per field
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Elena Zheleva · 1×
Citations per year

Countries citing papers authored by Ching‐man Au Yeung

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐man Au Yeung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching‐man Au Yeung. 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 Ching‐man Au Yeung. The network helps show where Ching‐man Au Yeung may publish in the future.

Co-authorship network of co-authors of Ching‐man Au Yeung

This figure shows the co-authorship network connecting the top 25 collaborators of Ching‐man Au Yeung. A scholar is included among the top collaborators of Ching‐man Au Yeung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ching‐man Au Yeung. Ching‐man Au Yeung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2
“Popularity Effect” in User-Generated Content: Evidence from Online Product Reviewsbreakdown →
314
3 3
4 16
5 32
6 1
7 4
8 56
9 9
10 43
11 1
12 28
13 16
14 41
15 41
16 17
17 3
18 6
19 0
20 2

About Ching‐man Au Yeung

Ching‐man Au Yeung is a scholar working on Statistical and Nonlinear Physics, Information Systems and Communication, having authored 27 papers that have together received 700 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Topic Modeling (7 papers) and Semantic Web and Ontologies (7 papers). The work is most often cited by research in Communication (125 citations), Information Systems and Management (79 citations) and Information Systems (243 citations). Ching‐man Au Yeung has collaborated with scholars based in United Kingdom, China and Japan. Frequent co-authors include Paulo Góes, Mingfeng Lin, Nigel Shadbolt, Nicholas Gibbins, Adam Jatowt, Tomoharu Iwata, Michael G. Noll, Katsumi Tanaka, Christoph Meinel and Kevin Duh. Their work appears in journals such as Information Systems Research, IEEE Intelligent Systems and Computational Intelligence.

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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