Robert Henderson


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A corpus of K’iche’ annotated for morphosyntactic structure
Francis Tyers | Robert Henderson
Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas

This article describes a collection of sentences in K’iche’ annotated for morphology and syntax. K’iche’ is a language in the Mayan language family, spoken in Guatemala. The annotation is done according to the guidelines of the Universal Dependencies project. The corpus consists of a total of 1,433 sentences containing approximately 10,000 tokens and is released under a free/open-source licence. We present a comparison of parsing systems for K’iche’ using this corpus and describe how it can be used for mining linguistic examples.


Social Meaning in Repeated Interactions
Elin McCready | Robert Henderson
Proceedings of the Probability and Meaning Conference (PaM 2020)

Judgements about communicative agents evolve over the course of interactions both in how individuals are judged for testimonial reliability and for (ideological) trustworthiness. This paper combines a theory of social meaning and persona with a theory of reliability within a game-theoretic view of communication, giving a formal model involving interactional histories, repeated game models and ways of evaluating social meaning and trustworthiness.

Towards functional, agent-based models of dogwhistle communication
Robert Henderson | Elin McCready
Proceedings of the Probability and Meaning Conference (PaM 2020)

Henderson and McCready 2017, 2018, 2019 build a novel theory of so-called ‘dogwhistle’ communication by extending the social meaning games of Burnett 2017. This work reports on an ongoing project to build systems to model the evolution of dogwhistle communication in a population based on probability monads (Erwig and Kollmansberger, 2006; Kidd, 2007). The ultimate results will be useful not just for dogwhistles, but modeling the diffusion and evolution of social meaning in populations in general. The initial results presented here is a computational implementation of Henderson and McCready 2018, which will serve as the basis for models with multiple speakers and repeated interactions.