Chih‐Ping Wei

3.3k total citations
109 papers, 2.2k citations indexed

About

Chih‐Ping Wei is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Chih‐Ping Wei has authored 109 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Artificial Intelligence, 41 papers in Information Systems and 16 papers in Sociology and Political Science. Recurrent topics in Chih‐Ping Wei's work include Text and Document Classification Technologies (23 papers), Advanced Text Analysis Techniques (20 papers) and Web Data Mining and Analysis (15 papers). Chih‐Ping Wei is often cited by papers focused on Text and Document Classification Technologies (23 papers), Advanced Text Analysis Techniques (20 papers) and Web Data Mining and Analysis (15 papers). Chih‐Ping Wei collaborates with scholars based in Taiwan, United States and Hong Kong. Chih‐Ping Wei's co-authors include Christopher C. Yang, Paul Jen‐Hwa Hu, Ting‐Peng Liang, Tsang-Hsiang Cheng, Yen‐Hsien Lee, Chin‐Sheng Yang, Shengsheng Xiao, Ming Dong, Olivia R. Liu Sheng and San‐Yih Hwang and has published in prestigious journals such as Computers in Human Behavior, Expert Systems with Applications and Information & Management.

In The Last Decade

Chih‐Ping Wei

102 papers receiving 2.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chih‐Ping Wei Taiwan 25 862 622 509 450 267 109 2.2k
Stephen Shaoyi Liao Hong Kong 26 871 1.0× 660 1.1× 282 0.6× 759 1.7× 183 0.7× 120 2.6k
Yezheng Liu China 21 504 0.6× 317 0.5× 433 0.9× 472 1.0× 133 0.5× 101 1.7k
Alan S. Abrahams United States 19 624 0.7× 581 0.9× 198 0.4× 524 1.2× 117 0.4× 72 1.7k
Guoqing Chen China 28 919 1.1× 778 1.3× 199 0.4× 469 1.0× 73 0.3× 156 2.4k
Sérgio Moro Portugal 30 905 1.0× 431 0.7× 886 1.7× 1.3k 2.9× 375 1.4× 113 3.2k
Kristof Coussement France 28 757 0.9× 633 1.0× 1.3k 2.6× 451 1.0× 601 2.3× 69 2.8k
Qing Cao United States 23 648 0.8× 294 0.5× 393 0.8× 820 1.8× 269 1.0× 60 2.6k
Jae Kyeong Kim South Korea 20 518 0.6× 1.2k 1.9× 432 0.8× 422 0.9× 91 0.3× 57 2.1k
Melody Y. Kiang United States 23 963 1.1× 307 0.5× 267 0.5× 311 0.7× 136 0.5× 60 2.4k
Vasant Dhar United States 23 882 1.0× 741 1.2× 354 0.7× 582 1.3× 79 0.3× 90 2.9k

Countries citing papers authored by Chih‐Ping Wei

Since Specialization
Citations

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

Fields of papers citing papers by Chih‐Ping Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chih‐Ping Wei. 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 Chih‐Ping Wei. The network helps show where Chih‐Ping Wei may publish in the future.

Co-authorship network of co-authors of Chih‐Ping Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Chih‐Ping Wei. A scholar is included among the top collaborators of Chih‐Ping Wei 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 Chih‐Ping Wei. Chih‐Ping Wei 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
1.
Wei, Chih‐Ping, Eric Fang, Chin‐Sheng Yang, & Pengfeï Liu. (2025). To shine or not to shine: Startup success prediction by exploiting technological and venture-capital-related features. Information & Management. 62(6). 104152–104152.
2.
Jiang, James J., Patrick Y.K. Chau, Brian Fitzgerald, et al.. (2022). Journey with Ting-Peng Liang in Pacific Asia Information Systems Field. Pacific Asia journal of the Association for Information Systems. 14. 5–17. 1 indexed citations
3.
Chen, Yuyuan, et al.. (2020). Partner Up: A Deep Learning Method for Predicting the Success of Social Media Influencer Collaboration. Journal of the Association for Information Systems. 1 indexed citations
4.
Liu, Kuan‐Hung, et al.. (2018). Alternative Ingredient Recommendation: A Co-occurrence and Ingredient Category Importance Based Approach. Journal of the Association for Information Systems. 5 indexed citations
5.
Peng, Chih-Hung, Dezhi Yin, Chih‐Ping Wei, & Han Zhang. (2017). Impact of Perspective Taking on Reviewer Behavior: A Multi-Method Exploration. Journal of the Association for Information Systems. 4966–4980. 3 indexed citations
6.
Peng, Chih-Hung, Dezhi Yin, Chih‐Ping Wei, & Han Zhang. (2014). How and When Review Length and Emotional Intensity Influence Review Helpfulness: Empirical Evidence from Epinions.com. Journal of the Association for Information Systems. 4(2). 232–7. 19 indexed citations
7.
Wei, Chih‐Ping, et al.. (2013). Exploiting poly-lingual documents for improving text categorization effectiveness. Decision Support Systems. 57. 64–76. 5 indexed citations
8.
Wei, Chih‐Ping, et al.. (2013). Mining Suppliers from Online News Documents. Pacific Asia Conference on Information Systems. 261. 1 indexed citations
9.
Wei, Chih‐Ping, et al.. (2012). Predicting The Helpfulness Of Online Product Reviewers: A Data Mining Approach. Pacific Asia Conference on Information Systems. 134. 2 indexed citations
10.
Wei, Chih‐Ping, et al.. (2011). Estimating Trust Strength For Supporting Effective Recommendation Services. Journal of the Association for Information Systems. 212.
11.
Hwang, San‐Yih, et al.. (2010). Combining Coauthorship Network and Content for Literature Recommendation. Journal of the Association for Information Systems. 40. 1 indexed citations
12.
Wang, Wenkai, et al.. (2010). Developing and Validating Service Innovation Readiness. Journal of the Association for Information Systems. 28(42). 71–59014. 2 indexed citations
13.
Lee, Yen‐Hsien, Chih‐Ping Wei, & Paul Jen‐Hwa Hu. (2007). Preserving User Preferences in Document-Category Management: An Ontology-based Evolution Approach. Journal of the Association for Information Systems. 64. 1 indexed citations
14.
Yang, Chin‐Sheng & Chih‐Ping Wei. (2007). Context-aware Document-clustering Technique. Journal of the Association for Information Systems. 65.
15.
Cheng, Tsang-Hsiang & Chih‐Ping Wei. (2006). Single-Class Learning for Spam Filtering: An Ensemble Approach. Journal of the Association for Information Systems. 62. 1 indexed citations
16.
Wei, Chih‐Ping, Chin‐Sheng Yang, & Chun-Neng Huang. (2006). Turning Online Product Reviews to Customer Knowledge: A Semantic-based Sentiment Classification Approach. Journal of the Association for Information Systems. 50. 6 indexed citations
17.
Hu, Paul Jen‐Hwa, Tsang-Hsiang Cheng, & Chih‐Ping Wei. (2005). Pharmacokinetic Data Mining for Managing Clinical Use of Vancomycin. Journal of the Association for Information Systems. 77. 1 indexed citations
18.
Wei, Chih‐Ping, et al.. (2004). Use of Text Summarization for Supporting Event Detection. Journal of the Association for Information Systems. 87. 3 indexed citations
19.
Wei, Chih‐Ping & Tsang-Hsiang Cheng. (2003). A Clustering-based Approach for Supporting Document-Category Integration. Journal of the Association for Information Systems. 91. 2 indexed citations
20.
Wei, Chih‐Ping & Yen‐Hsien Lee. (2001). Event Detection for Supporting Environmental Scanning:An Information Extraction-based Approach. Pacific Asia Conference on Information Systems. 62. 1 indexed citations

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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