Jin Yea Jang

22 total papers · 1.5k total citations
18 papers, 908 citations indexed

About

Jin Yea Jang is a scholar working on Sociology and Political Science, Artificial Intelligence and Communication. According to data from OpenAlex, Jin Yea Jang has authored 18 papers receiving a total of 908 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Sociology and Political Science, 10 papers in Artificial Intelligence and 5 papers in Communication. Recurrent topics in Jin Yea Jang's work include Misinformation and Its Impacts (7 papers), Speech and dialogue systems (6 papers) and Social Media and Politics (5 papers). Jin Yea Jang is often cited by papers focused on Misinformation and Its Impacts (7 papers), Speech and dialogue systems (6 papers) and Social Media and Politics (5 papers). Jin Yea Jang collaborates with scholars based in United States and South Korea. Jin Yea Jang's co-authors include Svitlana Volkova, Yejin Choi, Eunsol Choi, Hannah Rashkin, Nathan O. Hodas, Kyle Shaffer, Dongwon Lee, Kyungsik Han, Patrick C. Shih and San Kim and has published in prestigious journals such as Computer, Empirical Methods in Natural Language Processing and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

In The Last Decade

Jin Yea Jang

16 papers receiving 863 citations

Hit Papers

Truth of Varying Shades: ... 2017 2026 2020 2023 2017 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Jin Yea Jang 742 525 451 110 108 18 908
Naeemul Hassan 469 0.6× 402 0.8× 272 0.6× 118 1.1× 120 1.1× 37 825
Anastasia Giachanou 504 0.7× 583 1.1× 346 0.8× 81 0.7× 66 0.6× 37 912
Nadia Conroy 898 1.2× 453 0.9× 659 1.5× 150 1.4× 230 2.1× 8 1.0k
Niall Conroy 622 0.8× 358 0.7× 423 0.9× 96 0.9× 133 1.2× 7 727
Johannes Kiesel 454 0.6× 567 1.1× 375 0.8× 62 0.6× 80 0.7× 36 815
Pik-Mai Hui 585 0.8× 301 0.6× 437 1.0× 204 1.9× 90 0.8× 15 931
Giovanni Luca Ciampaglia 528 0.7× 306 0.6× 248 0.5× 177 1.6× 63 0.6× 28 763
Aditi Gupta 666 0.9× 298 0.6× 498 1.1× 197 1.8× 137 1.3× 37 969
Gabriel Magno 219 0.3× 337 0.6× 436 1.0× 103 0.9× 111 1.0× 14 734
Xichen Zhang 575 0.8× 357 0.7× 403 0.9× 94 0.9× 142 1.3× 29 802

Countries citing papers authored by Jin Yea Jang

Since Specialization
Citations

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

Fields of papers citing papers by Jin Yea Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin Yea Jang. 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 Jin Yea Jang. The network helps show where Jin Yea Jang may publish in the future.

Co-authorship network of co-authors of Jin Yea Jang

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Yea Jang. A scholar is included among the top collaborators of Jin Yea Jang 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 Jin Yea Jang. Jin Yea Jang 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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