Yung‐Chun Chang

1.9k total citations
79 papers, 1000 citations indexed

About

Yung‐Chun Chang is a scholar working on Artificial Intelligence, Molecular Biology and Sociology and Political Science. According to data from OpenAlex, Yung‐Chun Chang has authored 79 papers receiving a total of 1000 indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 17 papers in Molecular Biology and 8 papers in Sociology and Political Science. Recurrent topics in Yung‐Chun Chang's work include Topic Modeling (26 papers), Sentiment Analysis and Opinion Mining (20 papers) and Advanced Text Analysis Techniques (17 papers). Yung‐Chun Chang is often cited by papers focused on Topic Modeling (26 papers), Sentiment Analysis and Opinion Mining (20 papers) and Advanced Text Analysis Techniques (17 papers). Yung‐Chun Chang collaborates with scholars based in Taiwan, United States and Canada. Yung‐Chun Chang's co-authors include Chih‐Hao Ku, Ming‐Huei Chen, Liling Deng, Hsiang‐Cheng Chi, Chien‐Hung Chen, Chang-Shing Lee, Mei‐Hui Wang, Richard Tzong‐Han Tsai, Wen−Lian Hsu and Wen-Lian Hsu and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Yung‐Chun Chang

68 papers receiving 959 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yung‐Chun Chang Taiwan 15 418 307 144 141 126 79 1000
M. Saqib Nawaz China 13 208 0.5× 131 0.4× 63 0.4× 87 0.6× 33 0.3× 59 774
Zhiling Guo Singapore 18 71 0.2× 220 0.7× 78 0.5× 252 1.8× 292 2.3× 48 916
Punit Ahluwalia United States 10 150 0.4× 112 0.4× 56 0.4× 103 0.7× 39 0.3× 37 616
Zheng He China 18 87 0.2× 91 0.3× 46 0.3× 200 1.4× 128 1.0× 60 935
Efthimios Tambouris Greece 20 382 0.9× 291 0.9× 39 0.3× 64 0.5× 37 0.3× 116 1.5k
Anita Prinzie Belgium 16 133 0.3× 88 0.3× 21 0.1× 159 1.1× 195 1.5× 23 816
Peter A. Chow-White Canada 13 91 0.2× 194 0.6× 40 0.3× 102 0.7× 87 0.7× 24 968
Vassilios Peristeras Greece 18 439 1.1× 346 1.1× 24 0.2× 43 0.3× 48 0.4× 80 1.3k
Md Asadul Islam Malaysia 18 93 0.2× 109 0.4× 20 0.1× 246 1.7× 232 1.8× 77 947
Khalid Al‐Khatib Germany 21 553 1.3× 371 1.2× 13 0.1× 219 1.6× 71 0.6× 52 1.5k

Countries citing papers authored by Yung‐Chun Chang

Since Specialization
Citations

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

Fields of papers citing papers by Yung‐Chun Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yung‐Chun Chang. 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 Yung‐Chun Chang. The network helps show where Yung‐Chun Chang may publish in the future.

Co-authorship network of co-authors of Yung‐Chun Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Yung‐Chun Chang. A scholar is included among the top collaborators of Yung‐Chun Chang 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 Yung‐Chun Chang. Yung‐Chun Chang 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.
Shahid, Farah, Min‐Huei Hsu, Yung‐Chun Chang, & Wen‐Shan Jian. (2025). Using Generative AI to Extract Structured Information from Free Text Pathology Reports. Journal of Medical Systems. 49(1). 36–36. 1 indexed citations
2.
Chang, Yung‐Chun, et al.. (2025). Graph-aware pre-trained language model for political sentiment analysis in Filipino social media. Engineering Applications of Artificial Intelligence. 146. 110317–110317. 1 indexed citations
3.
Chang, Yung‐Chun, et al.. (2025). Extracting critical clinical indicators and survival prediction of lung cancer from pathology reports using large language models. Computers in Biology and Medicine. 195. 110621–110621.
4.
Ku, Chih‐Hao, Yung‐Chun Chang, & Yichuan Wang. (2024). How to strategically respond to online hotel reviews: A strategy-aware deep learning approach. Information & Management. 61(5). 103970–103970. 4 indexed citations
5.
Chang, Yung‐Chun, et al.. (2024). Leveraging enhanced BERT models for detecting suicidal ideation in Thai social media content amidst COVID-19. Information Processing & Management. 61(4). 103706–103706. 14 indexed citations
6.
Chang, Yung‐Chun, et al.. (2024). Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits. Journal of Biomedical Informatics. 155. 104657–104657. 5 indexed citations
7.
8.
Chen, Min-Chen, et al.. (2023). Clinical narrative-aware deep neural network for emergency department critical outcome prediction. Journal of Biomedical Informatics. 138. 104284–104284. 14 indexed citations
9.
Chen, Min-Chen, et al.. (2021). Numerical Relation Detection in Financial Tweets using Dependency-aware Deep Neural Network. International Conference on Computational Linguistics. 218–225. 1 indexed citations
10.
Tseng, Philip, Feng‐Jen Tsai, Jason C. Hsu, et al.. (2021). Public Awareness as a Line of Defense Against COVID-19 in Taiwan. Asia Pacific Journal of Public Health. 33(8). 981–982. 2 indexed citations
11.
12.
Chang, Yung‐Chun, et al.. (2017). Identifying Protein-protein Interactions in Biomedical Literature using Recurrent Neural Networks with Long Short-Term Memory. International Joint Conference on Natural Language Processing. 2. 240–245. 24 indexed citations
13.
Chang, Yung‐Chun, et al.. (2017). MONPA: Multi-objective Named-entity and Part-of-speech Annotator for Chinese using Recurrent Neural Network. International Joint Conference on Natural Language Processing. 2. 80–85. 4 indexed citations
14.
Chang, Yung‐Chun, et al.. (2016). PIPE: a protein–protein interaction passage extraction module for BioCreative challenge. Database. 2016. baw101–baw101. 26 indexed citations
15.
16.
Chang, Yung‐Chun, et al.. (2016). Sentiment analysis of Chinese microblog message using neural network-based vector representation for measuring Regional prejudice. Pacific Asia Conference on Information Systems. 307. 3 indexed citations
17.
Chang, Yung‐Chun, et al.. (2015). Semantic Frame-Based Approach for Reader-Emotion Detection. Journal of the Association for Information Systems. 162. 1 indexed citations
18.
Chang, Yung‐Chun, et al.. (2014). Semantic Frame-based Statistical Approach for Topic Detection. Waseda University Repository (Waseda University). 75–84. 1 indexed citations
19.
Chang, Yung‐Chun, et al.. (2013). TEMPTING system: A hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries. Journal of Biomedical Informatics. 46. S54–S62. 29 indexed citations
20.
Jiang, Mike Tian-Jian, Cheng‐Wei Lee, Chad Liu, Yung‐Chun Chang, & Wen−Lian Hsu. (2011). Robustness Analysis of Adaptive Chinese Input Methods. 53–61.

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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