Michael Chau

6.0k citations
153 papers · 3.7k · h-index 33

Impact in

    • Web Data Mining and Analysis
    • Data Mining Algorithms and Applications
    • Spam and Phishing Detection
    • Social Media and Politics

Papers in

Michael Chau

145 papers receiving 3.4k citations

Peers

Michael Chau
Comparison fields: 5 of 143
  • Information Systems 1.3k
  • Communication 381
  • Information Systems and Management 244
  • Artificial Intelligence 1.1k
  • Management Information Systems 286
Replace Hsinchun Chen with:
Hsinchun Chen United States
Yan Chen China
Virgı́lio Almeida Brazil
Jennifer Xu United States
Marcos André Gonçalves Brazil
Nigel Shadbolt United Kingdom
Ahmed Abbasi United States
David D. Clark United States
Jussara M. Almeida Brazil
Gobinda Chowdhury United Kingdom
Michael Chau relative to Hsinchun Chen United States Hsinchun Chen's profile →
Citations per field
00.5×1.5×
Hsinchun Chen · 1×
Citations per year

Countries citing papers authored by Michael Chau

Since Specialization
Citations

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

Fields of papers citing papers by Michael Chau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 153 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004329
2 2012257
3 2006195
4 2013153
5 2006141
6 2013129
7 2014120
8 2007105
9 200299
10 201385
11 200282
12 201878
13 202075
14 200566
15 200364
16 201364
17 200162
18 201359
19 200957
20 200457

About Michael Chau

Michael Chau is a scholar working on Information Systems, Artificial Intelligence, Sociology and Political Science, Communication and Statistical and Nonlinear Physics, having authored 153 papers that have together received 3.7k indexed citations. Recurring topics across this work include Web Data Mining and Analysis (35 papers), Complex Network Analysis Techniques (16 papers), Information Retrieval and Search Behavior (14 papers), Digital Marketing and Social Media (13 papers), Advanced Text Analysis Techniques (11 papers), Technology Adoption and User Behaviour (10 papers), Web visibility and informetrics (10 papers) and Data Management and Algorithms (9 papers). The work is most often cited by research in Information Systems (1.3k citations), Communication (381 citations), Information Systems and Management (244 citations), Artificial Intelligence (1.1k citations) and Management Information Systems (286 citations). Michael Chau has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Jennifer Xu, Hsinchun Chen, Xu, King‐Wa Fu, Daniel Zeng, Yi Qin, G. Alan Wang, Wingyan Chung, Tim M. H. Li and Chung‐hong Chan. Their work appears in journals such as Journal of the Association for Information Systems, Decision Support Systems, Information Systems Frontiers, MIS Quarterly and The Journal of Organic Chemistry.

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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