Jack Grieve

2.1k citations
60 papers · 1.1k · h-index 18

Impact in

Papers in

Jack Grieve

53 papers receiving 1.0k citations

Peers

Jack Grieve
Comparison fields: 5 of 78
  • Linguistics and Language 437
  • Language and Linguistics 355
  • Human-Computer Interaction 107
  • Communication 112
  • Artificial Intelligence 468
Replace Dawn Archer with:
Dawn Archer United Kingdom
Jesse Egbert United States
Václav Březina United Kingdom
Dirk Speelman Belgium
Eric Friginal United States
Elena Tognini-Bonelli Czechia
Pam Peters Australia
Vít Suchomel Czechia
Miloš Jakubíček Czechia
Vít Baisa Czechia
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Citations per field
00.5×3.3×
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Citations per year

Countries citing papers authored by Jack Grieve

Since Specialization
Citations

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

Fields of papers citing papers by Jack Grieve

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jack Grieve, 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 Jack Grieve Line = papers co-authored together Jack Grieve links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Analyzing Appraisal Automatically
2004141
2 2015108
3 201985
4 201170
5 201067
6 201652
7 201850
8 201648
9 201948
10 201748
11 201647
12 201427
13
A corpus-based regional dialect survey of grammatical variation in written standard American English
200923
14 202322
15 201121
16 201321
17 202121
18 200920
19 201316
20 201815

About Jack Grieve

Jack Grieve is a scholar working on Linguistics and Language, Language and Linguistics, Artificial Intelligence, Experimental and Cognitive Psychology and Sociology and Political Science, having authored 60 papers that have together received 1.1k indexed citations. Recurring topics across this work include Linguistic Variation and Morphology (32 papers), Authorship Attribution and Profiling (12 papers), Natural Language Processing Techniques (10 papers), Phonetics and Phonology Research (9 papers), Language, Discourse, Communication Strategies (8 papers), Hate Speech and Cyberbullying Detection (8 papers), Digital Communication and Language (6 papers) and Linguistics, Language Diversity, and Identity (5 papers). The work is most often cited by research in Linguistics and Language (437 citations), Language and Linguistics (355 citations), Human-Computer Interaction (107 citations), Communication (112 citations) and Artificial Intelligence (468 citations). Jack Grieve has collaborated with scholars based in United Kingdom, United States and Belgium. Frequent co-authors include Diansheng Guo, Maite Taboada, Isobelle Clarke, Andrea Nini, Dirk Geeraerts, Dirk Speelman, Yuan Huang, Alice Bee Kasakoff, Douglas Biber and Eric Friginal. Their work appears in journals such as Corpus Linguistics and Linguistic Theory, PLoS ONE, Language Variation and Change, American Speech and English Language and 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.

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