Eu-Gene Siew
Impact in
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- Technology Adoption and User Behaviour
- Management Information Systems top 10%
- Big Data and Business Intelligence
Papers in
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- Advanced Text Analysis Techniques 6
- Topic Modeling 5
- Algorithms and Data Compression 4
- Text and Document Classification Technologies 4
- Sentiment Analysis and Opinion Mining 3
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- Web Data Mining and Analysis 9
- Co-authors
- Paul H.P. Yeow (8 shared papers)Sylvester Olubolu Orimaye (6 shared papers)Yakub Sebastian (2 shared papers)Saadat M. Alhashmi (7 shared papers)Lay-Ki Soon (2 shared papers)Ramesh Kumar Ayyasamy (3 shared papers)Nicholas Grigoriou (1 shared paper)Joachim P. Sturmberg (1 shared paper)
In The Last Decade
Eu-Gene Siew
28 papers receiving 353 citations
Peers
Comparison fields: 5 of 69
- Information Systems and Management 110
- Management Information Systems 53
- Accounting 61
- Information Systems 105
- Artificial Intelligence 146
Countries citing papers authored by Eu-Gene Siew
This map shows the geographic impact of Eu-Gene Siew'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 Eu-Gene Siew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eu-Gene Siew more than expected).
Fields of papers citing papers by Eu-Gene Siew
This network shows the impact of papers produced by Eu-Gene Siew. 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 Eu-Gene Siew. The network helps show where Eu-Gene Siew may publish in the future.
Co-authors
The 17 scholars most cited alongside Eu-Gene Siew, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 83 | |
| 2 | 2012 | 60 | |
| 3 | 2009 | 35 | |
| 4 | 2017 | 30 | |
| 5 | 2016 | 27 | |
| 6 | 2023 | 19 | |
| 7 | Computer-assisted auditing tools acceptance using I-TOE: A new paradigm | 2012 | 17 |
| 8 | Adoption of audit technology in audit firms | 2013 | 16 |
| 9 | 2016 | 12 | |
| 10 | 2016 | 10 | |
| 11 | 2012 | 8 | |
| 12 | 2017 | 8 | |
| 13 | 2010 | 6 | |
| 14 | 2010 | 6 | |
| 15 | 2013 | 6 | |
| 16 | 2010 | 5 | |
| 17 | 2003 | 5 | |
| 18 | 2010 | 4 | |
| 19 | 2023 | 3 | |
| 20 | 2012 | 3 |
About Eu-Gene Siew
Eu-Gene Siew is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Information Systems and Management and Management Information Systems, having authored 32 papers that have together received 378 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (9 papers), Advanced Text Analysis Techniques (6 papers), Topic Modeling (5 papers), Caching and Content Delivery (5 papers), Technology Adoption and User Behaviour (5 papers), Algorithms and Data Compression (4 papers), Text and Document Classification Technologies (4 papers) and Sentiment Analysis and Opinion Mining (3 papers). The work is most often cited by research in Information Systems and Management (110 citations), Management Information Systems (53 citations), Accounting (61 citations), Information Systems (105 citations) and Artificial Intelligence (146 citations). Eu-Gene Siew has collaborated with scholars based in Malaysia, Australia and Vietnam. Frequent co-authors include Paul H.P. Yeow, Sylvester Olubolu Orimaye, Yakub Sebastian, Saadat M. Alhashmi, Lay-Ki Soon, Ramesh Kumar Ayyasamy, Nicholas Grigoriou, Joachim P. Sturmberg, Kate Smith‐Miles and Leonid Churilov. Their work appears in journals such as The Knowledge Engineering Review, PLoS ONE, International Journal of Accounting Information Systems, Applied Ergonomics and Data & Knowledge Engineering.
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.