Jing-Shin Chang

33 total papers · 500 total citations
27 papers, 350 citations indexed

About

Jing-Shin Chang is a scholar working on Artificial Intelligence, Molecular Biology and Language and Linguistics. According to data from OpenAlex, Jing-Shin Chang has authored 27 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 6 papers in Molecular Biology and 3 papers in Language and Linguistics. Recurrent topics in Jing-Shin Chang's work include Natural Language Processing Techniques (22 papers), Topic Modeling (14 papers) and Biomedical Text Mining and Ontologies (5 papers). Jing-Shin Chang is often cited by papers focused on Natural Language Processing Techniques (22 papers), Topic Modeling (14 papers) and Biomedical Text Mining and Ontologies (5 papers). Jing-Shin Chang collaborates with scholars based in Taiwan. Jing-Shin Chang's co-authors include Keh‐Yih Su, Yi‐Chung Lin, Shu‐Chuan Chen, Chao-Lin Liu and Mei-Hui Su and has published in prestigious journals such as Machine Translation, Meeting of the Association for Computational Linguistics and Computers and the Humanities.

In The Last Decade

Jing-Shin Chang

25 papers receiving 274 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jing-Shin Chang 325 41 39 27 25 27 350
Ahmed Guessoum 344 1.1× 28 0.7× 72 1.8× 42 1.6× 14 0.6× 29 400
Boontawee Suntisrivaraporn 314 1.0× 169 4.1× 104 2.7× 10 0.4× 32 1.3× 32 363
Jean-Pierre Chanod 276 0.8× 21 0.5× 41 1.1× 10 0.4× 14 0.6× 14 309
Simon Dobnik 309 1.0× 57 1.4× 33 0.8× 50 1.9× 6 0.2× 32 359
Chung Hee Hwang 365 1.1× 16 0.4× 32 0.8× 18 0.7× 3 0.1× 16 396
Wojciech Skut 359 1.1× 14 0.3× 24 0.6× 9 0.3× 17 0.7× 15 389
Marta Tatu 376 1.2× 30 0.7× 43 1.1× 11 0.4× 4 0.2× 16 395
Xabier Artola Zubillaga 263 0.8× 9 0.2× 29 0.7× 12 0.4× 6 0.2× 43 294
Ferran Plà 342 1.1× 32 0.8× 40 1.0× 24 0.9× 11 0.4× 42 401
Beate Dorow 325 1.0× 59 1.4× 38 1.0× 14 0.5× 10 0.4× 12 392

Countries citing papers authored by Jing-Shin Chang

Since Specialization
Citations

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

Fields of papers citing papers by Jing-Shin Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jing-Shin 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 Jing-Shin Chang. The network helps show where Jing-Shin Chang may publish in the future.

Co-authorship network of co-authors of Jing-Shin Chang

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

All Works

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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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