Nicholas Meade

406 citations
3 papers · 116 indexed · h-index 3
Topics
Topic Modeling (3 papers)Natural Language Processing Techniques (2 papers)Speech and dialogue systems (2 papers)
Journals
Transactions of the Association for Computational LinguisticsProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Partner nations
CanadaAlgeriaIsrael

In The Last Decade

Nicholas Meade

3 papers receiving 113 citations

Peers

Nicholas Meade
Comparison fields: 5 of 35
  • Artificial Intelligence 89
  • Computer Vision and Pattern Recognition 14
  • Information Systems 11
  • Safety Research 10
  • Health Informatics 8
Replace Miruna Clinciu with:
Miruna Clinciu United Kingdom
Jasmijn Bastings United States
Eva Vanmassenhove Netherlands
Phu Mon Htut United States
Potsawee Manakul United Kingdom
Tosin Adewumi Sweden
Miryam de Lhoneux Sweden
Yew Ken Chia Singapore
Arjun Roy Germany
Ayesha Bajwa Hong Kong
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Citations per field
00.5×2.9×
Miruna Clinciu · 1×
Citations per year

Countries citing papers authored by Nicholas Meade

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Meade

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicholas Meade

This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Meade. A scholar is included among the top collaborators of Nicholas Meade based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nicholas Meade. Nicholas Meade is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

3 of 3 papers shown
#WorkIndexed citations
1 30
2 6
3 80

About Nicholas Meade

Nicholas Meade is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Education, having authored 3 papers that have together received 116 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Health Informatics (8 citations), Artificial Intelligence (89 citations) and General Social Sciences (7 citations). Nicholas Meade has collaborated with scholars based in Canada, Algeria and Israel. Frequent co-authors include Siva Reddy, Yang Liu, Dilek Hakkani-Tür, Spandana Gella, Di Jin, Prakhar Gupta and Devamanyu Hazarika. Their work appears in journals such as Transactions of the Association for Computational Linguistics and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

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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