Jordan Kodner
Impact in
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- Language and cultural evolution
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- Syntax, Semantics, Linguistic Variation
Papers in
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- Natural Language Processing Techniques 11
- Topic Modeling 6
- Speech and dialogue systems 4
- Speech Recognition and Synthesis 2
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- Phonetics and Phonology Research 3
- Co-authors
- Charles Yang (3 shared papers)Shyam Upadhyay (1 shared paper)Dan Roth (1 shared paper)Salam Khalifa (4 shared papers)Hongzhi Xu (3 shared papers)Mitchell P. Marcus (3 shared papers)Sarah R. Payne (1 shared paper)Justin L. Mott (1 shared paper)
- Journals
- Natural Language & Linguistic Theory (1 paper)Cognition (1 paper)First Language (1 paper)Language Resources and Evaluation (1 paper)Glossa a journal of general linguistics (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Jordan Kodner
11 papers receiving 46 citations
Peers
Comparison fields: 5 of 19
- Cultural Studies 12
- Language and Linguistics 12
- Artificial Intelligence 31
- Linguistics and Language 4
- Experimental and Cognitive Psychology 8
Countries citing papers authored by Jordan Kodner
This map shows the geographic impact of Jordan Kodner'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 Jordan Kodner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordan Kodner more than expected).
Fields of papers citing papers by Jordan Kodner
This network shows the impact of papers produced by Jordan Kodner. 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 Jordan Kodner. The network helps show where Jordan Kodner may publish in the future.
Co-authors
The 12 scholars most cited alongside Jordan Kodner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 12 | |
| 2 | 2020 | 11 | |
| 3 | 2019 | 5 | |
| 4 | 2022 | 4 | |
| 5 | 2020 | 4 | |
| 6 | Morphological Segmentation for Low Resource Languages | 2020 | 3 |
| 7 | 2022 | 3 | |
| 8 | 2020 | 3 | |
| 9 | 2023 | 2 | |
| 10 | 2018 | 2 | |
| 11 | 2022 | 1 | |
| 12 | 2017 | 1 | |
| 13 | 2023 | 0 | |
| 14 | 2020 | 0 | |
| 15 | 2025 | 0 | |
| 16 | 2023 | 0 | |
| 17 | Language Acquisition In The Past | 2020 | 0 |
About Jordan Kodner
Jordan Kodner is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology, Cultural Studies, Linguistics and Language and Developmental and Educational Psychology, having authored 17 papers that have together received 51 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (11 papers), Topic Modeling (6 papers), Speech and dialogue systems (4 papers), Language and cultural evolution (3 papers), Phonetics and Phonology Research (3 papers), Linguistic Variation and Morphology (2 papers), Language Development and Disorders (2 papers) and Speech Recognition and Synthesis (2 papers). The work is most often cited by research in Cultural Studies (12 citations), Language and Linguistics (12 citations), Artificial Intelligence (31 citations), Linguistics and Language (4 citations) and Experimental and Cognitive Psychology (8 citations). Jordan Kodner has collaborated with scholars based in United States and China. Frequent co-authors include Charles Yang, Shyam Upadhyay, Dan Roth, Salam Khalifa, Hongzhi Xu, Mitchell P. Marcus, Sarah R. Payne, Justin L. Mott, Owen Rambow and Zhengxiang Wang. Their work appears in journals such as Natural Language & Linguistic Theory, Cognition, First Language, Language Resources and Evaluation and Glossa a journal of general linguistics.
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.