Chun-Neng Huang
- Artificial Intelligence top 10%
- Management Science and Operations Research top 5%
- Finance top 10%
- Information Systems top 10%
- Economics and Econometrics top 10%
- Co-authors
- Yulei ZhangHsinchun ChenRobert P. SchumakerTianjun FuChin‐Sheng YangChih‐Ping WeiNancy RobertsCatherine Larson
- Topics
- Spam and Phishing Detection (4 papers)Text and Document Classification Technologies (3 papers)Web Data Mining and Analysis (2 papers)
- Journals
- Journal of Management Information SystemsDecision Support SystemsJournal of the Association for Information Systems
- Partner nations
- United StatesTaiwan
In The Last Decade
Chun-Neng Huang
8 papers receiving 325 citations
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 162
- Management Science and Operations Research 161
- Finance 87
- Information Systems 78
- Economics and Econometrics 72
Countries citing papers authored by Chun-Neng Huang
This map shows the geographic impact of Chun-Neng Huang'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 Chun-Neng Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun-Neng Huang more than expected).
Fields of papers citing papers by Chun-Neng Huang
This network shows the impact of papers produced by Chun-Neng Huang. 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 Chun-Neng Huang. The network helps show where Chun-Neng Huang may publish in the future.
Co-authorship network of co-authors of Chun-Neng Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Chun-Neng Huang. A scholar is included among the top collaborators of Chun-Neng Huang 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 Chun-Neng Huang. Chun-Neng Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 224 | |
| 2 | 11 | |
| 3 | 27 | |
| 4 | 40 | |
| 5 | Sentiment Analysis of Financial News Articles 1 | 7 |
| 6 | 9 | |
| 7 | 22 | |
| 8 | Turning Online Product Reviews to Customer Knowledge: A Semantic-based Sentiment Classification Approach | 6 |
About Chun-Neng Huang
Chun-Neng Huang is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research, having authored 8 papers that have together received 346 indexed citations. Recurring topics across this work include Spam and Phishing Detection (4 papers), Text and Document Classification Technologies (3 papers) and Web Data Mining and Analysis (2 papers). The work is most often cited by research in Management Science and Operations Research (161 citations), Finance (87 citations) and Artificial Intelligence (162 citations). Chun-Neng Huang has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Yulei Zhang, Hsinchun Chen, Robert P. Schumaker, Tianjun Fu, Hsinchun Chen, Chin‐Sheng Yang, Chih‐Ping Wei, Nancy Roberts, Hsinchun Chen and Catherine Larson. Their work appears in journals such as Journal of Management Information Systems, Decision Support Systems and Journal of the Association for Information Systems.
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.