Michael Pearce

845 citations
35 papers · 469 · h-index 11

Impact in

Papers in

Michael Pearce

30 papers receiving 420 citations

Peers

Michael Pearce
Comparison fields: 5 of 72
  • Library and Information Sciences 29
  • Linguistics and Language 51
  • Language and Linguistics 73
  • Computer Networks and Communications 155
  • Information Systems 146
Replace Lawrence Jones with:
Lawrence Jones United States
Rosa Lorés Sanz Spain
Madelaine Plauché United States
Zhong Sun China
Brendan Flanagan Japan
Ludovic Tanguy France
Orphée De Clercq Belgium
Toshio Okamoto Japan
Hussein Suleman South Africa
Serkan Çelık Türkiye
Michael Pearce relative to Lawrence Jones United States Lawrence Jones's profile →
Citations per field
00.5×4.7×
Lawrence Jones · 1×
Citations per year

Countries citing papers authored by Michael Pearce

Since Specialization
Citations

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

Fields of papers citing papers by Michael Pearce

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Michael Pearce, 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 Michael Pearce Line = papers co-authored together Michael Pearce 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 2013109
2 200870
3 201446
4 200343
5 201037
6 200728
7 200525
8 200918
9 201915
10 200111
11 200411
12 20119
13 20156
14 20105
15 20135
16 20115
17 20123
18 20063
19 20182
20 20062

About Michael Pearce

Michael Pearce is a scholar working on Computer Networks and Communications, Linguistics and Language, Language and Linguistics, Computer Vision and Pattern Recognition and Sociology and Political Science, having authored 35 papers that have together received 469 indexed citations. Recurring topics across this work include Linguistic Variation and Morphology (8 papers), Peer-to-Peer Network Technologies (5 papers), Lexicography and Language Studies (5 papers), Caching and Content Delivery (4 papers), Mobile Ad Hoc Networks (4 papers), Linguistics, Language Diversity, and Identity (3 papers), Cooperative Communication and Network Coding (3 papers) and Multilingual Education and Policy (3 papers). The work is most often cited by research in Library and Information Sciences (29 citations), Linguistics and Language (51 citations), Language and Linguistics (73 citations), Computer Networks and Communications (155 citations) and Information Systems (146 citations). Michael Pearce has collaborated with scholars based in United States, United Kingdom and New Zealand. Frequent co-authors include Ray Hunt, Sherali Zeadally, Bogdan Cărbunar, Venu Vasudevan, Yang Yu, Weidong Shi, Sarah Williams, Sherali Zeadally, Rahul Potharaju and N. Narasimhan. Their work appears in journals such as English Today, Language and Literature International Journal of Stylistics, Journal of English Linguistics, Australasian Journal of Paramedicine and IEEE Internet Computing.

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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