Ching Nam Hang

407 total citations
12 papers, 202 citations indexed

About

Ching Nam Hang is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Ching Nam Hang has authored 12 papers receiving a total of 202 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Information Systems and 3 papers in Sociology and Political Science. Recurrent topics in Ching Nam Hang's work include Topic Modeling (3 papers), Online Learning and Analytics (2 papers) and Misinformation and Its Impacts (2 papers). Ching Nam Hang is often cited by papers focused on Topic Modeling (3 papers), Online Learning and Analytics (2 papers) and Misinformation and Its Impacts (2 papers). Ching Nam Hang collaborates with scholars based in Singapore, Taiwan and Hong Kong. Ching Nam Hang's co-authors include Chee Wei Tan, Pei-Duo Yu, M.F. Wong, Siu‐Wai Ho, Roberto Morabito, Yao‐Wen Huang, Chung-Hung Tsai, Dong-Hyun Lee, Sy‐Yen Kuo and Fang Yu and has published in prestigious journals such as IEEE Access, IEEE Journal of Biomedical and Health Informatics and Entropy.

In The Last Decade

Ching Nam Hang

11 papers receiving 191 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ching Nam Hang Singapore	8	100	62	27	25	22	12	202
Hongye Jin United States	2	128 1.3×	41 0.7×	24 0.9×	8 0.3×	28 1.3×	2	241
Yannis Katsis United States	10	193 1.9×	49 0.8×	37 1.4×	10 0.4×	17 0.8×	31	299
Mohammed Y. Shakor Iraq	6	149 1.5×	62 1.0×	20 0.7×	61 2.4×	131 6.0×	15	314
Sruti Srinivasa Ragavan United States	7	55 0.6×	86 1.4×	21 0.8×	66 2.6×	21 1.0×	13	191
Viet-Man Le Austria	8	79 0.8×	86 1.4×	18 0.7×	9 0.4×	4 0.2×	27	164
Yeganeh Kordi United States	1	191 1.9×	39 0.6×	13 0.5×	7 0.3×	17 0.8×	2	269
Max Hort United Kingdom	7	119 1.2×	58 0.9×	29 1.1×	12 0.5×	15 0.7×	18	240
Nigar M. Shafiq Surameery Iraq	5	149 1.5×	40 0.6×	12 0.4×	58 2.3×	129 5.9×	13	301
Varun Kumar United States	8	119 1.2×	49 0.8×	14 0.5×	26 1.0×	5 0.2×	19	179
Timo Schick Germany	9	412 4.1×	50 0.8×	12 0.4×	10 0.4×	14 0.6×	13	466

Countries citing papers authored by Ching Nam Hang

Since Specialization

Citations

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

Fields of papers citing papers by Ching Nam Hang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching Nam Hang. 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 Nam Hang. The network helps show where Ching Nam Hang may publish in the future.

Co-authorship network of co-authors of Ching Nam Hang

This figure shows the co-authorship network connecting the top 25 collaborators of Ching Nam Hang. A scholar is included among the top collaborators of Ching Nam Hang 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 Nam Hang. Ching Nam Hang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Hang, Ching Nam, Pei-Duo Yu, & Chee Wei Tan. (2025). TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checking. IEEE Transactions on Artificial Intelligence. 6(11). 3148–3162. 8 indexed citations

2.

Hang, Ching Nam, Pei-Duo Yu, & Chee Wei Tan. (2024). TrumorGPT: Query Optimization and Semantic Reasoning over Networks for Automated Fact-Checking. 1–6. 11 indexed citations

3.

Hang, Ching Nam, Pei-Duo Yu, Roberto Morabito, & Chee Wei Tan. (2024). Large Language Models Meet Next-Generation Networking Technologies: A Review. Future Internet. 16(10). 365–365. 22 indexed citations

4.

Hang, Ching Nam, Chee Wei Tan, & Pei-Duo Yu. (2024). MCQGen: A Large Language Model-Driven MCQ Generator for Personalized Learning. IEEE Access. 12. 102261–102273. 37 indexed citations

5.

Wong, M.F., et al.. (2023). Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review. Entropy. 25(6). 888–888. 53 indexed citations

6.

Hang, Ching Nam, et al.. (2023). Privacy-Enhancing Digital Contact Tracing with Machine Learning for Pandemic Response: A Comprehensive Review. Big Data and Cognitive Computing. 7(2). 108–108. 13 indexed citations

7.

Hang, Ching Nam, et al.. (2023). MEGA: Machine Learning-Enhanced Graph Analytics for Infodemic Risk Management. IEEE Journal of Biomedical and Health Informatics. 27(12). 6100–6111. 14 indexed citations

8.

Tan, Chee Wei, et al.. (2022). A Chatbot-Server Framework for Scalable Machine Learning Education through Crowdsourced Data. 271–274. 4 indexed citations

9.

Tan, Chee Wei, et al.. (2020). Mathematics Gamification in Mobile App Software for Personalized Learning at Scale. 1–5. 6 indexed citations

10.

Hang, Ching Nam, et al.. (2018). Parallel Counting of Triangles in Large Graphs: Pruning and Hierarchical Clustering Algorithms. 36. 1–6. 2 indexed citations

11.

Huang, Yao‐Wen, Fang Yu, Ching Nam Hang, et al.. (2004). Verifying Web applications using bounded model checking. 199–208. 31 indexed citations

12.

Hang, Ching Nam. (1983). THE MAXIMUM SIZE OF A CRIT- ICAL 2-EDGE-CONNECTED GRAPH. 科学通报(英文版). 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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