James Thorne

1.5k citations
35 papers · 645 · h-index 15

Impact in

Papers in

    • Topic Modeling 11
    • Natural Language Processing Techniques 9
    • Hate Speech and Cyberbullying Detection 3
    • Speech and dialogue systems 2
    • Syntax, Semantics, Linguistic Variation 6
    • Historical Linguistics and Language Studies 2

James Thorne

32 papers receiving 556 citations

Peers

James Thorne
Comparison fields: 5 of 58
  • Language and Linguistics 158
  • Artificial Intelligence 388
  • Linguistics and Language 39
  • Experimental and Cognitive Psychology 81
  • Information Systems 148
Replace Philip Edmonds with:
Philip Edmonds United Kingdom
Keh-Jiann Chen Taiwan
Jan Odijk Netherlands
Hans van Halteren Netherlands
Stelios Piperidis Greece
Bente Mægaard Denmark
Lori Levin United States
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Citations per field
00.5×2×4×6×8×9.3×
Philip Edmonds · 1×
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 21 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 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 196983
2 201870
3 201869
4 201758
5 202152
6 196538
7 196838
8 201932
9 202129
10 196626
11 201926
12 201919
13 196817
14 196717
15 196915
16 201712
17 19698
18 20236
19 20226
20 19835

About James Thorne

James Thorne is a scholar working on Artificial Intelligence, Language and Linguistics, Experimental and Cognitive Psychology, Sociology and Political Science and Information Systems, having authored 35 papers that have together received 645 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (9 papers), Syntax, Semantics, Linguistic Variation (6 papers), Hate Speech and Cyberbullying Detection (3 papers), Misinformation and Its Impacts (3 papers), Language, Metaphor, and Cognition (3 papers), Historical Linguistics and Language Studies (2 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Language and Linguistics (158 citations), Artificial Intelligence (388 citations), Linguistics and Language (39 citations), Experimental and Cognitive Psychology (81 citations) and Information Systems (148 citations). James Thorne has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Andreas Vlachos, Arpit Mittal, Christos Christodoulopoulos, Zeerak Talat, Joachim Bingel, Oana Cocarascu, Paul Bratley, Xiaoxuan Wang, Mingjie Chen and Michael Schlichtkrull. Their work appears in journals such as Journal of Linguistics, Nature, Soil Science Society of America Journal, Proceedings of the VLDB Endowment and Language.

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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