Yohan Jo

1.7k total citations · 2 hit papers
31 papers, 1.0k citations indexed

About

Yohan Jo is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications. According to data from OpenAlex, Yohan Jo has authored 31 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 6 papers in Information Systems and 4 papers in Computer Science Applications. Recurrent topics in Yohan Jo's work include Topic Modeling (15 papers), Natural Language Processing Techniques (10 papers) and Sentiment Analysis and Opinion Mining (7 papers). Yohan Jo is often cited by papers focused on Topic Modeling (15 papers), Natural Language Processing Techniques (10 papers) and Sentiment Analysis and Opinion Mining (7 papers). Yohan Jo collaborates with scholars based in United States, United Kingdom and South Korea. Yohan Jo's co-authors include Alice Oh, Carolyn Penstein Rosé, Oliver Ferschke, Gaurav Singh Tomar, Dragan Gašević, Il‐Chul Moon, Chris Reed, Eduard Hovy, Hyeju Jang and Seungwhan Moon and has published in prestigious journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics and Discovery Research Portal (University of Dundee).

In The Last Decade

Yohan Jo

26 papers receiving 960 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Aspect and sentiment unification model for online review analysis

2011 497 citations Yohan Jo et al. profile →
Proceedings of the 9th International Conference on Educational Data Mining (EDM 2016)

2016 270 citations Yohan Jo, Gaurav Singh Tomar et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yohan Jo United States	12	745	227	165	142	82	31	1.0k
Álvaro Ortigosa Spain	15	632 0.8×	348 1.5×	391 2.4×	143 1.0×	198 2.4×	44	1.1k
Dan Goldwasser United States	23	1.1k 1.4×	256 1.1×	213 1.3×	239 1.7×	46 0.6×	88	1.5k
Ștefan Trăușan-Matu Romania	16	313 0.4×	203 0.9×	188 1.1×	129 0.9×	207 2.5×	145	836
Swapna Somasundaran United States	17	1.2k 1.6×	198 0.9×	33 0.2×	125 0.9×	32 0.4×	35	1.3k
Denis Helić Austria	16	236 0.3×	316 1.4×	181 1.1×	133 0.9×	80 1.0×	124	881
Rebecca Bruce United States	15	1.3k 1.7×	223 1.0×	57 0.3×	83 0.6×	25 0.3×	43	1.5k
Maria Soledad Pera United States	15	423 0.6×	454 2.0×	71 0.4×	118 0.8×	67 0.8×	117	805
Torsten Zesch Germany	25	1.6k 2.2×	313 1.4×	82 0.5×	53 0.4×	74 0.9×	117	1.8k
Toine Bogers Denmark	15	446 0.6×	671 3.0×	156 0.9×	128 0.9×	22 0.3×	91	1.0k
Angelika Maag Australia	7	476 0.6×	213 0.9×	125 0.8×	96 0.7×	31 0.4×	22	795

Countries citing papers authored by Yohan Jo

Since Specialization

Citations

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

Fields of papers citing papers by Yohan Jo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yohan Jo. 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 Yohan Jo. The network helps show where Yohan Jo may publish in the future.

Co-authorship network of co-authors of Yohan Jo

This figure shows the co-authorship network connecting the top 25 collaborators of Yohan Jo. A scholar is included among the top collaborators of Yohan Jo 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 Yohan Jo. Yohan Jo 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:

20 of 20 papers shown

1.

Kim, Doyoun, et al.. (2025). Knowledge Tracing in Programming Education Integrating Students’ Questions. 27703–27718.

2.

Kim, Ju‐Hee, et al.. (2025). Dialogue Systems for Emotional Support via Value Reinforcement. 28733–28766.

3.

Kim, Sungdong, et al.. (2025). Ask Optimal Questions: Aligning Large Language Models with Retriever’s Preference in Conversation. 5899–5921. 1 indexed citations

4.

Jo, Yohan, et al.. (2025). The Open Argument Mining Framework. Discovery Research Portal (University of Dundee). 318–328. 1 indexed citations

5.

Lee, Gyubok, Seng Chan You, Seung-Jin Baek, et al.. (2024). Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes. 5148–5168. 8 indexed citations

6.

Jo, Yohan, et al.. (2024). Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information. 1809–1820.

7.

Jo, Yohan, et al.. (2023). FactKG: Fact Verification via Reasoning on Knowledge Graphs. 16190–16206. 13 indexed citations

8.

Jo, Yohan, Xinyan Zhao, Arijit Biswas, et al.. (2023). Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users. 3237–3269.

9.

Jo, Yohan, et al.. (2023). Open-WikiTable : Dataset for Open Domain Question Answering with Complex Reasoning over Table. 8285–8297. 2 indexed citations

10.

Jo, Yohan, et al.. (2023). KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models. 9410–9421. 14 indexed citations

11.

Jo, Yohan, et al.. (2023). From Values to Opinions: Predicting Human Behaviors and Stances Using Value-Injected Large Language Models. 15539–15559. 2 indexed citations

12.

Jo, Yohan, et al.. (2022). Argument Mining for Review Helpfulness Prediction. 8914–8922. 2 indexed citations

13.

Jo, Yohan, Elijah Mayfield, Chris Reed, & Eduard Hovy. (2020). Machine-Aided Annotation for Fine-Grained Proposition Types in Argumentation. Language Resources and Evaluation. 1008–1018. 4 indexed citations

14.

Jo, Yohan, Seojin Bang, Emaad Manzoor, Eduard Hovy, & Chris Reed. (2020). Detecting Attackable Sentences in Arguments. 1–23. 14 indexed citations

15.

Naik, Aakanksha, et al.. (2019). Using Functional Schemas to Understand Social Media Narratives. 22–33. 4 indexed citations

16.

Jo, Yohan, et al.. (2017). Roles and Success in Wikipedia Talk Pages: Identifying Latent Patterns of Behavior. International Joint Conference on Natural Language Processing. 1. 1026–1035. 5 indexed citations

17.

Jo, Yohan, et al.. (2017). Modeling Dialogue Acts with Content Word Filtering and Speaker Preferences. PubMed. 2017. 2179–2189. 6 indexed citations

18.

Rosé, Carolyn Penstein, Pierre Dillenbourg, Yohan Jo, et al.. (2016). Analytics of Social Processes in Learning Contexts: a Multi-level Perspective. International Conference of Learning Sciences. 24–31. 1 indexed citations

19.

Jang, Hyeju, et al.. (2016). Metaphor Detection with Topic Transition, Emotion and Cognition in Context. 216–225. 15 indexed citations

20.

Jang, Hyeju, Seungwhan Moon, Yohan Jo, & Carolyn Penstein Rosé. (2015). Metaphor Detection in Discourse. 384–392. 21 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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