Matthew Honnibal

30 total papers · 1.2k total citations
19 papers, 693 citations indexed

About

Matthew Honnibal is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Matthew Honnibal has authored 19 papers receiving a total of 693 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 3 papers in Information Systems and 3 papers in Management Science and Operations Research. Recurrent topics in Matthew Honnibal's work include Natural Language Processing Techniques (18 papers), Topic Modeling (16 papers) and Speech and dialogue systems (4 papers). Matthew Honnibal is often cited by papers focused on Natural Language Processing Techniques (18 papers), Topic Modeling (16 papers) and Speech and dialogue systems (4 papers). Matthew Honnibal collaborates with scholars based in Australia, United States and Israel. Matthew Honnibal's co-authors include Mark Johnson, James Curran, Joel Nothman, Ben Hachey, Will Radford, Yoav Goldberg, Irena Koprinska, Johan Bos, Jonathan K. Kummerfeld and Robert Dale and has published in prestigious journals such as Artificial Intelligence, Transactions of the Association for Computational Linguistics and Theory and applications of categories.

In The Last Decade

Matthew Honnibal

17 papers receiving 606 citations

Hit Papers

An Improved Non-monotonic... 2015 2026 2018 2022 2015 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matthew Honnibal 561 92 67 54 43 19 693
Jana Straková 638 1.1× 60 0.7× 58 0.9× 33 0.6× 40 0.9× 15 767
Aly A. Fahmy 465 0.8× 199 2.2× 57 0.9× 60 1.1× 49 1.1× 24 736
Karën Fort 263 0.5× 98 1.1× 50 0.7× 74 1.4× 22 0.5× 31 601
Tejaswini Deoskar 578 1.0× 94 1.0× 29 0.4× 105 1.9× 68 1.6× 17 714
Tommaso Caselli 627 1.1× 74 0.8× 29 0.4× 30 0.6× 58 1.3× 75 687
Daniel Duma 489 0.9× 101 1.1× 24 0.4× 65 1.2× 31 0.7× 13 792
Wei-Yun Ma 662 1.2× 125 1.4× 76 1.1× 72 1.3× 56 1.3× 42 782
Melanie Martin 531 0.9× 102 1.1× 35 0.5× 12 0.2× 21 0.5× 34 765
Jialong Han 473 0.8× 114 1.2× 49 0.7× 97 1.8× 23 0.5× 24 711
Jonathon Read 585 1.0× 119 1.3× 19 0.3× 20 0.4× 36 0.8× 26 679

Countries citing papers authored by Matthew Honnibal

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Honnibal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Honnibal

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Honnibal. A scholar is included among the top collaborators of Matthew Honnibal 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 Matthew Honnibal. Matthew Honnibal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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