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Corpus Linguistics and Linguistic Theory

Founded by Gries, Stefan Th. / Stefanowitsch, Anatol

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Dependency profiles in the large-scale analysis of discourse connectives

Veronika Laippala / Aki-Juhani Kyröläinen
  • Department of linguistics and languages, McMaster University, Hamilton, ON, Canada
  • Applied Linguistics, Brock University, St. Catharines, ON, Canada
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/ Jenna Kanerva / Filip Ginter
Published Online: 2018-06-06 | DOI: https://doi.org/10.1515/cllt-2017-0031

Abstract

This article presents dependency profiles (DPs) as an empirical method to investigate linguistic elements and their application to the study of 24 discourse connectives in the 3.7-billion token Finnish Internet Parsebank (http://bionlp-www.utu.fi/dep_search/). DPs are based on co-occurrence patterns of the discourse connectives with dependency syntax relations. They follow the assumption of usage-based models, according to which the semantic and functional properties of linguistic expressions arise based on their distributional characteristics. We focus on the typical usage patterns reflected by the DPs and the (dis)similarities among discourse connectives that these patterns reveal. We demonstrate that 1) DPs can be analyzed with clustering to obtain linguistically meaningful groupings among the connectives and that 2) the clustering can be combined with support vector machines to obtain generic and stable linguistic characteristics of the discourse connectives. We show that this data-driven method offers support for previous results and reveals novel tendencies outside the scope of studies on smaller corpora. As the method is based on automatic syntactic analysis following the cross-linguistic universal dependencies, it does not require manual annotation and can be applied to a number of languages and in contrastive studies.

Keywords: Dependency syntax; discourse connectives; web-as-corpus; Universal dependencies

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About the article

Veronika Laippala

Veronika Laippala is Associate professor of Digital linguistics in the School of languages and translation studies at the University of Turku, Finland. Her research focuses on corpus linguistics and computational linguistics. In particular, she has worked on the development of web-crawled corpora and corpora of computer-mediated communication in various languages and on enhancing computational methods for text linguistics and discourse analysis. Her most recent projects include “Finnish Internet Parsebank” developing a very large web-corpus for Finnish and “Structuring language use across multilingual web corpora” aiming at automatically detecting registers from web corpora in different languages.

Aki-Juhani Kyröläinen

Aki-Juhani Kyröläinen is currently a post-doctoral fellow at McMaster University and Brock University within the Words in the World project. His main research interests center on distributional models of language with a focus on morphosyntactic structures. Additionally, his research combines multiple methodologies ranging from corpus analysis to psycholinguistic experimentation with an emphasis on eye-tracking.​

Jenna Kanerva

Jenna Kanerva has a MSc in computer science and she is currently a PhD student at the University of Turku. Her research focuses on machine learning methods in language technology, main interest area being development of dependency parsing pipeline for Finnish.

Filip Ginter

Filip Ginter gained MSc (2001) and PhD (2007) in computer science and currently holds the position of an assistant professor in language technology at the University of Turku. His research interests are centered around machine learning applied to large textual corpora.


Published Online: 2018-06-06


Citation Information: Corpus Linguistics and Linguistic Theory, ISSN (Online) 1613-7035, ISSN (Print) 1613-7027, DOI: https://doi.org/10.1515/cllt-2017-0031.

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