Part of
Corpus-based Approaches to Register Variation
Edited by Elena Seoane and Douglas Biber
[Studies in Corpus Linguistics 103] 2021
► pp. 291312
References (43)
References
Barron, Alexander T. J., Huang, Jenny, Spang, Rebecca L. & DeDeo, Simon. 2018. Individuals, institutions, and innovation in the debates of the French Revolution. Proceedings of the National Academy of Sciences 115(18): 4607–4612. DOI logoGoogle Scholar
Biber, Douglas & Finegan, Edward. 1989. Drift and the evolution of English style: A history of three genres. Language 65(3): 487–517. DOI logoGoogle Scholar
Biber, Douglas & Gray, Bethany. 2011. The historical shift of scientific academic prose in English towards less explicit styles of expression: Writing without verbs. In Researching Specialized Languages [Studies in Corpus Linguistics 47], Vijay Bhatia, Purificación Sa´nchez & Pascual Pe´rez-Paredes (eds), 11–24. Amsterdam: John Benjamins. DOI logoGoogle Scholar
. 2013. Nominalizing the verb phrase in academic science writing. In The Verb Phrase in English: Investigating Recent Language Change with Corpora, Bas Aarts, Joanne Close, Geoffrey Leech & Sean Wallis (eds), 99–132. Cambridge: CUP. DOI logoGoogle Scholar
. 2016. Grammatical Complexity in Academic English: Linguistic Change in Writing. Cambridge: CUP. DOI logoGoogle Scholar
Bizzoni, Yuri, Degaetano-Ortlieb, Stefania, Fankhauser, Peter & Teich, Elke. 2020. Linguistic variation and change in 250 years of English scientific writing: A data-driven approach. Frontiers in Artificial Intelligence, section Language and Computation. DOI logoGoogle Scholar
Bochkarev, Vladimir, Solovyev, Valery D. & Wichmann, Soren. 2014. Universals versus historical contingencies in lexical evolution. Journal of The Royal Society Interface 11(101): 1–8. DOI logoGoogle Scholar
Culpeper, Jonathan & Kytö, Merja. 2010. Early Modern English Dialogues: Spoken Interaction as Writing. Cambridge: CUP.Google Scholar
Degaetano-Ortlieb, Stefania, Kermes, Hannah, Khamis, Ashraf & Teich, Elke. 2019. An information-theoretic approach to modeling diachronic change in scientific English. In From Data to Evidence in English Language Research, Carla Suhr, Terttu Nevalainen & Irma Taavitsainen (eds), 258–281. Leiden: Brill.Google Scholar
Degaetano-Ortlieb, Stefania & Piper, Andrew. 2019. The scientization of literary study. In Proceedings of the 3nd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature at NAACL, 18–28, Minneapolis, MN, June. East Stroudsburg PA: ACL. DOI logoGoogle Scholar
Degaetano-Ortlieb, Stefania & Teich, Elke. 2018. Using relative entropy for detection and analysis of periods of diachronic linguistic change. In Proceedings of the 2nd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature at COLING, 22–33, Santa Fe, NM, September. East Stroudsburg PA: ACL.Google Scholar
. 2019. Toward an optimal code for communication: The case of scientific English. Corpus Linguistics and Linguistic, 1–33. DOI logoGoogle Scholar
Delogu, Francesca, Crocker, Matthew & Drenhaus, Heiner. 2017. Teasing apart coercion and surprisal: Evidence from ERPs and eye-movements. Cognition 116: 49–59. DOI logoGoogle Scholar
Fankhauser, Peter, Knappen, Jörg & Teich, Elke. 2014. Exploring and visualizing variation in language resources. In Proceedings of the 9th Language Resources and Evaluation Conference (LREC), 4125–4128, Reykjavik, Iceland, May.Google Scholar
Fischer, Stefan, Knappen, Jörg, Menzel, Katrin & Teich, Elke. 2020. The Royal Society Corpus 6.0. Providing 300+ years of scientific writing for humanistic study. In Proceedings of the 15th Language Resources and Evaluation Conference (LREC), 794–802, Marseille, France, May.Google Scholar
Garg, Nikhil, Schiebinger, Londa, Jurafsky, Dan & Zou, James. 2018. Word embeddings quantify 100 years of gender and ethnic stereotypes. Proceedings of the National Academy of Sciences 115(16): 3635–3644. DOI logoGoogle Scholar
Gray, Bethany & Biber, Douglas. 2018. Academic writing as a locus of grammatical change: The development of phrasal complexity features. In Diachronic Corpora, Genre, and Language Change [Studies in Corpus Linguistics 85], Richard J. Whitt (ed.), 117–146. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Halliday, Michael A. K. 1985. Written and Spoken Language. Melbourne: Deakin University Press.Google Scholar
1988. On the language of physical science. In Registers of Written English: Situational Factors and Linguistic Features, Mohsen Ghadessy (ed.), 162–177. London: Pinter.Google Scholar
Halliday, Michael A. K. & Martin, James R. 1993. Writing Science: Literacy and Discursive Power. London: Falmer Press.Google Scholar
Hamilton, William L., Leskovec, Jure & Jurafsky, Dan. 2016. Cultural shift or linguistic drift? Comparing two computational models of semantic change. In Proceedings of the Empirical Methods in Natural Language Processing (EMNLP), 2116–2121, Austin, Texas, November.Google Scholar
Harris, Zellig. 1991. A Theory of Language and Information. A Mathematical Approach. Oxford: Clarendon Press.Google Scholar
Hawkins, Robert D., Goodman, Noah D., Goldberg, Adele E. & Griffiths, Thomas L. 2020. Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks. In Proceedings of the 42nd Virtual Annual Conference of the Cognitive Science Society.Google Scholar
Hilpert, Martin & Gries, Stefan T. 2016. Quantitative approaches to diachronic corpus linguistics. In The Cambridge Handbook of English Historical Linguistics, Merja Kytö & Päivi Pahta (eds), 36–53. Cambridge: CUP. DOI logoGoogle Scholar
Hilpert, Martin & Mair, Christian. 2015. Grammatical change. In The Cambridge Handbook of Corpus Linguistics, Douglas Biber & Randi Reppen (eds), 180–200. Cambridge: CUP. DOI logoGoogle Scholar
Kawaguchi, Yuji, Minegishi, Makoto & Viereck, Wolfgang. 2011. Corpus-based Analysis and Diachronic Linguistics [Tokyo University of Foreign Studies 3]. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Kermes, Hannah, Degaetano-Ortlieb, Stefania, Khamis, Ashraf, Knappen, Jörg & Teich, Elke. 2016. The Royal Society Corpus: From uncharted data to corpus. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC), 1928–1931, Portorož, Slovenia, May.Google Scholar
Klingenstein, Sara, Hitchcock, Tim & DeDeo, Simon. 2014. The civilizing process in London’s Old Bailey. Proceedings of the National Academy of Sciences 111(26): 9419–9424. DOI logoGoogle Scholar
Kopaczyk, Joanna. 2013. The Legal Language of Scottish Burghs: Standardization and Lexical Bundles. Oxford: OUP. DOI logoGoogle Scholar
Levy, Roger P. 2008. Expectation-based syntactic comprehension. Cognition 106(3): 1126–1177. DOI logoGoogle Scholar
Levy, Roger P. & Jaeger, Tim Florian. 2007. Speakers optimize information density through syntactic reduction. In Advances in Neural Information Processing Systems 19, Bernhard Schölkopf, John Platt & Thomas Hoffman (eds), 849–856. Cambridge MA: The MIT Press.Google Scholar
Mair, Christian. 2006. Twentieth-century English: History, Variation and Standardization. Cambridge: CUP. DOI logoGoogle Scholar
McNamara, Danielle S. 2001. Reading both high and low coherence texts: Effects of text sequence and prior knowledge. Canadian Journal of Experimental Psychology 55(1): 51–62. DOI logoGoogle Scholar
McNamara, Danielle S., Kintsch, Eileen, Butler Songer, Nancy & Kintsch, Walter. 1996. Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction 14(1): 1–43. DOI logoGoogle Scholar
Michel, Jean-Baptiste, Shen, Yuan Kui, Presser Aiden, Aviva, Veres, Adrian, Gray, Matthew K., Pickett, Joseph P., Hoiberg, Dale, Clancy, Dan, Norvig, Peter, Orwant, Jon, Pinker, Steven, Nowak, Martin A. & Lieberman Aiden, Erez. 2011. Quantitative analysis of culture using millions of digitized books. Science 331(6014): 176–182. DOI logoGoogle Scholar
Muralidharan, Aditi & Hearst, Marti A. 2013. Supporting exploratory text analysis in literature study. Literary and Linguistic Computing 28(2): 283–295. DOI logoGoogle Scholar
Nevalainen, Terttu & Closs Traugott, Elizabeth. 2012. The Oxford Handbook of the History of English. Oxford: OUP. DOI logoGoogle Scholar
Quirk, Randolph, Greenbaum, Sidney, Leech, Geoffrey & Svartvik, Jan. 1985. A Comprehensive Grammar of the English Language. London: Longman.Google Scholar
Rubino, Raphael, Degaetano-Ortlieb, Stefania, Teich, Elke & van Genabith, Josef. 2016. Modeling diachronic change in scientific writing with information density. In Proceedings of the 26th International Conference on Computational Linguistics (COLING), 750–761, Osaka, Japan, December.Google Scholar
Schulz, Erika, Oh, Yoon Mi, Malisz, Zofia, Andreeva, Bistra & Möbius, Bernd. 2016. Impact of prosodic structure and information density on vowel space size. In Proceedings of Speech Prosody, 350–354, Boston, MA, USA, May. DOI logoGoogle Scholar
Sikos, Les, Greenberg, Clayton, Drenhaus, Heiner & Crocker, Matthew. 2017. Information density of encodings: The role of syntactic variation in comprehension. In Proceedings of the 39th Annual Conference of the Cognitive Science Society, 3168–3173, London, UK, July.Google Scholar
Teich, Elke, Degaetano-Ortlieb, Stefania, Fankhauser, Peter, Kermes, Hannah & Lapshinova-Koltunski, Ekaterina. 2016. The linguistic construal of disciplinarity: A data mining approach using register features. Journal of the Association for Information Science and Technology (JASIST) 67(7): 1668–1678. DOI logoGoogle Scholar
Zhai, Chengxiang & Lafferty, John. 2004. A study of smoothing methods for language models applied to information retrieval. ACM Transactions on Information Systems 22(2): 179–214. DOI logoGoogle Scholar