James Thorne

1.5k citations
29 papers · 505 · h-index 13

Impact in

Papers in

    • Topic Modeling 11
    • Natural Language Processing Techniques 9
    • Speech and dialogue systems 2
    • Advanced Text Analysis Techniques 2
    • Syntax, Semantics, Linguistic Variation 5
    • Historical Linguistics and Language Studies 2

James Thorne

26 papers receiving 434 citations

Peers

James Thorne
Comparison fields: 5 of 54
  • Language and Linguistics 135
  • Artificial Intelligence 284
  • Linguistics and Language 28
  • Experimental and Cognitive Psychology 73
  • Information Systems 111
Replace Adrian Brașoveanu with:
Adrian Brașoveanu Austria
Lou Burnard United Kingdom
Pranav Anand United States
Hans Karlgren Sweden
Philip Edmonds United Kingdom
Jan Odijk Netherlands
Carol Van Ess-Dykema United States
Lori Levin United States
Klaus Ries United States
Hans van Halteren Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by James Thorne

Since Specialization
Citations

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

Fields of papers citing papers by James Thorne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside James Thorne, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with James Thorne Line = papers co-authored together James Thorne links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 196971
2 201862
3 201749
4 202146
5 196535
6 196834
7 201930
8 202128
9 196625
10 201925
11 201919
12 196716
13 196912
14 196810
15 201710
16 19698
17 20234
18 19654
19 20224
20 19834

About James Thorne

James Thorne is a scholar working on Artificial Intelligence, Language and Linguistics, Sociology and Political Science, Experimental and Cognitive Psychology and Information Systems, having authored 29 papers that have together received 505 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (9 papers), Syntax, Semantics, Linguistic Variation (5 papers), Misinformation and Its Impacts (3 papers), Historical Linguistics and Language Studies (2 papers), Speech and dialogue systems (2 papers), Linguistic Variation and Morphology (2 papers) and Advanced Text Analysis Techniques (2 papers). The work is most often cited by research in Language and Linguistics (135 citations), Artificial Intelligence (284 citations), Linguistics and Language (28 citations), Experimental and Cognitive Psychology (73 citations) and Information Systems (111 citations). James Thorne has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Andreas Vlachos, Christos Christodoulopoulos, Arpit Mittal, Oana Cocarascu, Paul Bratley, Mingjie Chen, Xiaoxuan Wang, Michael Schlichtkrull, Zhijiang Guo and Majid Yazdani. Their work appears in journals such as Journal of Linguistics, Nature, Language, Proceedings of the VLDB Endowment and Historia.

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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