Mapping Languages: The Corpus of Global Language Use

Dunn, J. (2020). “Mapping Languages: The Corpus of Global Language Use.” Language Resources and Evaluation. 54: 999-1018. Abstract. This paper describes a web-based corpus of global language use with a focus on how this corpus can be used for data-driven language mapping. First, the corpus provides a representation of where national varieties of major languages … More Mapping Languages: The Corpus of Global Language Use

Geographically-Balanced Gigaword Corpora for 50 Language Varieties

Dunn, J. & Adams, B. (2020). “Geographically-Balanced Gigaword Corpora for 50 Language Varieties.” In Proceedings of the Language Resources and Evaluation Conference. European Language Resources Association. 2528-2536. Abstract. While text corpora have been steadily increasing in overall size, even very large corpora are not designed to represent global population demographics. For example, recent work has … More Geographically-Balanced Gigaword Corpora for 50 Language Varieties

Global Syntactic Variation in Seven Languages

Dunn, J. (2019). “Global Syntactic Variation in Seven Languages: Towards a Computational Dialectology.” In Frontiers in Artificial Intelligence: Language and Computation. Abstract. The goal of this paper is to provide a complete representation of regional linguistic variation on a global scale. To this end, the paper focuses on removing three constraints that have previously limited … More Global Syntactic Variation in Seven Languages

Mapping Languages and Demographics

Dunn, J. and Adams, B. (2019). “Mapping Languages and Demographics with Georeferenced Corpora.” In Proceedings of Geocomputation 2019. Abstract. This paper evaluates large georeferenced corpora, taken from both web-crawled and social media sources, against ground-truth population and language-census datasets. The goal is to determine (i) which dataset best represents population demographics; (ii) in what parts … More Mapping Languages and Demographics

Modeling Global Syntactic Variation in English

Dunn, J. (2019). “Modeling Global Syntactic Variation in English Using Dialect Classification.” In Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects (NAACL 19). Association for Computational Linguistics. 42-53. Abstract. This paper evaluates global-scale dialect identification for 14 national varieties of English as a means for studying syntactic variation. The paper … More Modeling Global Syntactic Variation in English

Frequency vs. Association in Usage-Based Grammar

Dunn, J. (2019). “Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar.” In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (NAACL 19). Association for Computational Linguistics. 117-128. Abstract. A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This … More Frequency vs. Association in Usage-Based Grammar

Ontological and Grammatical Constraints on Metaphor Productivity

Dunn, J. (2020). “Ontological and Grammatical Constraints on Metaphor Productivity.” In Attardo, S. (ed.), Script-Based Semantics Foundations and Applications. Essays in Honor of Victor Raskin. De Gruyter: 55-76. Abstract. Traditional approaches view metaphor as a semantic/pragmatic phenomenon that occurs at a conceptual level as mappings between independent concepts. These conceptual mappings are then lexicalized into … More Ontological and Grammatical Constraints on Metaphor Productivity

Gradient Semantic Intuitions of Metaphoric Expressions

Dunn, J. (2011). “Gradient Semantic Intuitions of Metaphoric Expressions.” Metaphor & Symbol, 26(1): 53-67. Abstract. Metaphoric expressions are not all equal, in the sense that some are intuitively more or less metaphoric than others. Part of this intuition is influenced by the underlying metaphor, but another part is influenced by the linguistic expression which carries … More Gradient Semantic Intuitions of Metaphoric Expressions

What Metaphor Identification Systems Can Tell Us About Metaphor-in-Language

Dunn, J. (2013). “What Metaphor Identification Systems Can Tell Us About Metaphor-in-Language.” In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: First Workshop on Metaphor in NLP (NAACL 2013). Stroudsburg, PA: Association for Computational Linguistics. 1-10. Abstract. This paper evaluates four metaphor identification systems on the 200,000 word … More What Metaphor Identification Systems Can Tell Us About Metaphor-in-Language

Evaluating the Premises and Results of Metaphor Identification Systems

Dunn, J. (2013). “Evaluating the Premises and Results of Four Metaphor Identification Systems.” In Proceedings of the Conference on Intelligent Text Processing and Computational Linguistics, Vol. 1 (CICLING 2013). Heidelberg: Springer. 471-486. Abstract. This study first examines the implicit and explicit premises of four systems for identifying metaphoric utterances from unannotated input text. All four … More Evaluating the Premises and Results of Metaphor Identification Systems