Huahai Yang

30 papers receiving 700 citations

Peers

Huahai Yang
Comparison fields: 5 of 75
  • Artificial Intelligence 397
  • Sociology and Political Science 150
  • Information Systems 146
  • Human-Computer Interaction 121
  • Social Psychology 117
Replace Pratyush Kumar with:
Pratyush Kumar India
Jofish Kaye United States
Georg Groh Germany
Alice Oh South Korea
Sameer Patil United States
W. Randolph Ford United States
Tongshuang Wu United States
Jaime Arguello United States
Rosa Gil Spain
Huahai Yang relative to Pratyush Kumar India Pratyush Kumar's profile →
Citations per field
00.5×7.4×
Pratyush Kumar · 1×
Citations per year

Countries citing papers authored by Huahai Yang

Since Specialization
Citations

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

Fields of papers citing papers by Huahai Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huahai Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Huahai Yang. A scholar is included among the top collaborators of Huahai Yang 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 Huahai Yang. Huahai Yang 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
#WorkIndexed citations
1 2
2 113
3
Building Real-World Chatbot Interviewers: Lessons from a Wizard-of-Oz Field Study.
6
4 100
5 9
6 35
7 0
8 35
9 17
10 11
11 5
12
WizIE: A Best Practices Guided Development Environment for Information Extraction
12
13 2
14 29
15
Enabling domain-awareness for a generic natural language interface
5
16 35
17 96
18
Support spatial awareness: Collaborative navigation in a virtual environment.
1
19 2
20 1

About Huahai Yang

Huahai Yang is a scholar working on Human-Computer Interaction, Computer Science Applications and Artificial Intelligence, having authored 31 papers that have together received 757 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Speech and dialogue systems (5 papers) and Usability and User Interface Design (5 papers). The work is most often cited by research in Human-Computer Interaction (121 citations), Health Informatics (23 citations) and Applied Psychology (70 citations). Huahai Yang has collaborated with scholars based in United States, China and Argentina. Frequent co-authors include Michelle X. Zhou, Yunyao Li, Gloria Mark, H. V. Jagadish, Jingyi Jessica Li, Liang Gou, Wenxi Chen, Ziang Xiao, Q. Vera Liao and Gary M. Olson. Their work appears in journals such as ACM Transactions on Database Systems, ACM Transactions on Computer-Human Interaction and ACM Transactions on Interactive Intelligent Systems.

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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