Michael Gamon

7.9k total citations · 2 hit papers
85 papers, 3.9k citations indexed

About

Michael Gamon is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Michael Gamon has authored 85 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Artificial Intelligence, 18 papers in Information Systems and 8 papers in Statistical and Nonlinear Physics. Recurrent topics in Michael Gamon's work include Topic Modeling (48 papers), Natural Language Processing Techniques (36 papers) and Text Readability and Simplification (16 papers). Michael Gamon is often cited by papers focused on Topic Modeling (48 papers), Natural Language Processing Techniques (36 papers) and Text Readability and Simplification (16 papers). Michael Gamon collaborates with scholars based in United States, United Kingdom and India. Michael Gamon's co-authors include Anthony Aue, Patrick Pantel, Scott Counts, Munmun De Choudhury, Eric Horvitz, Chris Brockett, Martin Chodorow, Joel Tetreault, Claudia Leacock and Kristina Toutanova and has published in prestigious journals such as PLoS ONE, Language Testing and CALICO Journal.

In The Last Decade

Michael Gamon

83 papers receiving 3.5k citations

Hit Papers

Representing Text for Joint Embedding of Text and Knowled... 2015 2026 2018 2022 2015 2021 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Gamon United States 33 3.1k 704 441 324 283 85 3.9k
Diana Inkpen Canada 27 2.7k 0.9× 552 0.8× 478 1.1× 252 0.8× 122 0.4× 155 3.3k
Philip Resnik United States 40 5.6k 1.8× 784 1.1× 538 1.2× 292 0.9× 151 0.5× 158 7.1k
Emre Kıcıman United States 26 963 0.3× 670 1.0× 535 1.2× 538 1.7× 198 0.7× 99 2.8k
David Milne Australia 19 1.9k 0.6× 639 0.9× 268 0.6× 339 1.0× 79 0.3× 52 2.9k
Dirk Hovy Italy 28 3.0k 1.0× 519 0.7× 348 0.8× 374 1.2× 78 0.3× 112 3.5k
Fábio Crestani Switzerland 27 2.0k 0.7× 1.6k 2.3× 197 0.4× 441 1.4× 225 0.8× 238 3.3k
Svetlana Kiritchenko Canada 27 4.2k 1.4× 720 1.0× 391 0.9× 673 2.1× 318 1.1× 52 5.0k
Catherine Havasi United States 18 3.4k 1.1× 589 0.8× 311 0.7× 364 1.1× 163 0.6× 39 4.1k
Maarten Sap United States 25 1.9k 0.6× 217 0.3× 705 1.6× 498 1.5× 106 0.4× 70 2.9k
Paolo Rosso Spain 41 6.0k 2.0× 1.8k 2.5× 549 1.2× 1.1k 3.3× 205 0.7× 339 7.1k

Countries citing papers authored by Michael Gamon

Since Specialization
Citations

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

Fields of papers citing papers by Michael Gamon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Gamon

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

All Works

20 of 20 papers shown
1.
Dı́az, Fernando, Michael Gamon, Jake M. Hofman, Emre Kıcıman, & David Rothschild. (2016). Online and Social Media Data As an Imperfect Continuous Panel Survey. PLoS ONE. 11(1). e0145406–e0145406. 81 indexed citations
2.
Wang, Helen J., Michael Gamon, Shamsi T. Iqbal, et al.. (2015). The activity platform. 22–22. 1 indexed citations
3.
Toutanova, Kristina, Danqi Chen, Patrick Pantel, et al.. (2015). Representing Text for Joint Embedding of Text and Knowledge Bases. 1499–1509. 401 indexed citations breakdown →
4.
Mansour, Riham, et al.. (2013). Revisiting the Old Kitchen Sink: Do we Need Sentiment Domain Adaptation?. Recent Advances in Natural Language Processing. 420–427. 5 indexed citations
5.
Kıcıman, Emre, Munmun De Choudhury, Scott Counts, Michael Gamon, & Bo Thiesson. (2013). Analyzing Social Media Relationships in Context with Discussion Graphs. VBN Forskningsportal (Aalborg Universitet). 1 indexed citations
6.
Quirk, Chris, Pallavi Choudhury, Jianfeng Gao, et al.. (2012). MSR SPLAT, a language analysis toolkit. North American Chapter of the Association for Computational Linguistics. 21–24. 21 indexed citations
7.
Pantel, Patrick, Thomas Lin, & Michael Gamon. (2012). Mining Entity Types from Query Logs via User Intent Modeling. Meeting of the Association for Computational Linguistics. 1. 563–571. 34 indexed citations
8.
Sajjad, Hassan, Patrick Pantel, & Michael Gamon. (2012). Underspecified Query Refinement via Natural Language Question Generation. International Conference on Computational Linguistics. 2341–2356. 6 indexed citations
9.
Artzi, Yoav, Patrick Pantel, & Michael Gamon. (2012). Predicting Responses to Microblog Posts. North American Chapter of the Association for Computational Linguistics. 602–606. 61 indexed citations
10.
Quirk, Chris, Pallavi Choudhury, Michael Gamon, & Lucy Vanderwende. (2011). MSR-NLP Entry in BioNLP Shared Task 2011. Meeting of the Association for Computational Linguistics. 155–163. 23 indexed citations
11.
Gamon, Michael. (2011). High-Order Sequence Modeling for Language Learner Error Detection. 180–189. 17 indexed citations
12.
Gamon, Michael. (2010). Using mostly native data to correct errors in learners' writing: a meta-classifier approach. North American Chapter of the Association for Computational Linguistics. 163–171. 45 indexed citations
13.
Gamon, Michael. (2010). Using Mostly Native Data to Correct Errors in Learners' Writing. North American Chapter of the Association for Computational Linguistics. 163–171. 39 indexed citations
14.
Gamon, Michael, Jianfeng Gao, Chris Brockett, et al.. (2008). Using Contextual Speller Techniques and Language Modeling for ESL Error Correction. International Joint Conference on Natural Language Processing. 449–456. 107 indexed citations
15.
Aue, Anthony & Michael Gamon. (2005). Customizing Sentiment Classifiers to New Domains: a Case Study. Recent Advances in Natural Language Processing. 244 indexed citations
16.
Corston-Oliver, Simon, Eric K. Ringger, Michael Gamon, & Richard Campbell. (2004). Integration of Email and Task Lists.. 7 indexed citations
17.
Gamon, Michael, et al.. (2003). French Amalgam: a quick adaptation of a sentence realization system to French. Conference of the European Chapter of the Association for Computational Linguistics. 323–330. 1 indexed citations
18.
Corston-Oliver, Simon, Michael Gamon, Eric K. Ringger, & Robert C. Moore. (2002). An Overview of Amalgam: A Machine-learned Generation Module. 33–40. 30 indexed citations
19.
Gamon, Michael. (1997). The derivational formation of chain-links : minimalism and binding theory. UMI eBooks. 1 indexed citations
20.
Gamon, Michael. (1990). Testing pressure sensitive adhesives.. 73(3). 106–107. 3 indexed citations

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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