Peter Graff

651 total citations
14 papers, 204 citations indexed

About

Peter Graff is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Peter Graff has authored 14 papers receiving a total of 204 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Cognitive Neuroscience and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Peter Graff's work include Natural Language Processing Techniques (5 papers), Neurobiology of Language and Bilingualism (4 papers) and Phonetics and Phonology Research (4 papers). Peter Graff is often cited by papers focused on Natural Language Processing Techniques (5 papers), Neurobiology of Language and Bilingualism (4 papers) and Phonetics and Phonology Research (4 papers). Peter Graff collaborates with scholars based in United States, Canada and United Kingdom. Peter Graff's co-authors include T. Florian Jaeger, William Croft, Morgan Sonderegger, Edward Gibson, Kyle Mahowald, Maria Polinsky, Richard Futrell, Adam Albright, Timothy J. O’Donnell and Gillian Gallagher and has published in prestigious journals such as Cognition, Language and Lingua.

In The Last Decade

Peter Graff

12 papers receiving 189 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Graff United States 6 92 75 68 66 58 14 204
Gertraud Fenk-Oczlon Austria 8 68 0.7× 70 0.9× 42 0.6× 80 1.2× 56 1.0× 20 188
Yoon Mi Oh France 7 80 0.9× 68 0.9× 47 0.7× 30 0.5× 30 0.5× 11 196
Grant McGuire United States 8 218 2.4× 69 0.9× 105 1.5× 56 0.8× 28 0.5× 19 257
Márton Sóskuthy Canada 10 199 2.2× 69 0.9× 125 1.8× 55 0.8× 24 0.4× 18 244
Ashwini Deo United States 9 94 1.0× 75 1.0× 64 0.9× 184 2.8× 23 0.4× 21 258
Yu‐Ying Chuang Germany 7 88 1.0× 106 1.4× 36 0.5× 69 1.0× 34 0.6× 18 219
Abby Kaplan United States 7 187 2.0× 77 1.0× 152 2.2× 94 1.4× 55 0.9× 11 233
Antje Schweitzer Germany 10 193 2.1× 152 2.0× 92 1.4× 65 1.0× 15 0.3× 38 275
Anne Pycha United States 9 176 1.9× 93 1.2× 83 1.2× 53 0.8× 19 0.3× 24 248
Laura Staum Casasanto United States 8 106 1.2× 54 0.7× 101 1.5× 129 2.0× 20 0.3× 15 229

Countries citing papers authored by Peter Graff

Since Specialization
Citations

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

Fields of papers citing papers by Peter Graff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Graff

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

All Works

14 of 14 papers shown
1.
2.
Sonderegger, Morgan, et al.. (2017). The Medium-Term Dynamics of Accents on Reality Television. Language. 93(3). 598–640. 34 indexed citations
3.
Futrell, Richard, Adam Albright, Peter Graff, & Timothy J. O’Donnell. (2017). A Generative Model of Phonotactics. Transactions of the Association for Computational Linguistics. 5. 73–86. 16 indexed citations
4.
Sonderegger, Morgan, et al.. (2017). The medium-term dynamics of accents on reality television: Supplementary Material. Language. 93(3). 2 indexed citations
5.
Mahowald, Kyle, et al.. (2016). SNAP Judgments: A Small n Acceptability Paradigm (SNAP) for Linguistic Acceptability Judgments. Language. 92(3). 619–635. 27 indexed citations
6.
Mahowald, Kyle, et al.. (2016). SNAP judgments: A small N acceptability paradigm (SNAP) for linguistic acceptability judgments: Online Appendices. Language. 92(3). s1–s14. 2 indexed citations
7.
Graff, Peter. (2014). Communicative Efficiency in the Lexicon. DSpace@MIT (Massachusetts Institute of Technology). 10 indexed citations
8.
Gibson, Edward, Pauline Jacobson, Peter Graff, et al.. (2014). A Pragmatic Account of Complexity in Definite Antecedent-Contained-Deletion Relative Clauses. Journal of Semantics. 32(4). 579–618. 2 indexed citations
9.
Scontras, Gregory, Peter Graff, & Noah D. Goodman. (2012). Comparing pluralities. Cognition. 123(1). 190–197. 2 indexed citations
10.
Gallagher, Gillian & Peter Graff. (2011). The role of similarity in phonology. Lingua. 122(2). 107–111. 4 indexed citations
11.
Jaeger, T. Florian, et al.. (2011). Mixed effect models for genetic and areal dependencies in linguistic typology. Linguistic Typology. 15(2). 76 indexed citations
12.
Polinsky, Maria, et al.. (2011). Subject preference and ergativity. Lingua. 122(3). 267–277. 27 indexed citations
13.
D’Souza, Desmond & Peter Graff. (1995). Working with OMT: Model Integration.. Journal of Object-oriented Programming. 7. 23–29. 1 indexed citations
14.
Graff, Peter. (1977). Die Wirtschaftsprognose : Empirie und Theorie, Voraussetzungen und Konsequenzen. Mohr eBooks. 1 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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