Cover not available
Part of
Diachronic Corpora, Genre, and Language Change
Edited by Richard J. Whitt
[Studies in Corpus Linguistics 85] 2018
► pp. 41–64

Diachronic collocations, genre, and DiaCollo

| Berlin-Brandenburgische Akademie der Wissenschaften

This chapter presents the formal basis for diachronic collocation profiling as implemented in the open-source software tool “DiaCollo” and sketches some potential applications to multi-genre diachronic corpora. Explicitly developed for the efficient extraction, comparison, and interactive visualization of collocations from a diachronic text corpus, DiaCollo is suitable for processing collocation pairs whose association strength depends on extralinguistic features such as the date of occurrence or text genre. By tracking changes in a word’s typical collocates over time, DiaCollo can help to provide a clearer picture of diachronic changes in the word’s usage, especially those related to semantic shift or discourse environment. Use of the flexible DDC search engine back-end allows user queries to make explicit reference to genre and other document-level metadata, thus allowing e.g. independent genre-local profiles or cross-genre comparisons. In addition to traditional static tabular display formats, a web-service plugin also offers a number of intuitive interactive online visualizations for diachronic profile data for immediate inspection.

Article outline
  • 1.Introduction
  • 2.Related work
  • 3.Implementation
    • 3.1Overview
    • 3.2Corpus data
    • 3.3Co-occurrence frequencies
      • 3.3.1Native co-occurrence relation
      • 3.3.2Term × document matrix co-occurrence relation
      • 3.3.3DDC co-occurrence relation
    • 3.4Scoring and pruning
    • 3.5Comparisons
    • 3.6Output & visualization
  • 4.Examples
    • 4.1Adjectival attribution: What makes a “man”?
    • 4.2Pronominal adverbs and deictic locality
  • 5.Conclusion
  • Notes
  • References
Published online: 8 November 2018
DOI logo
https://doi.org/10.1075/scl.85.03jur
References
Baker, Paul, Gabrielatos, Costas, Khosravinik, Majid, Krzyżanowski, Michał, McEnery, Tony & Wodak, Ruth
2008 A useful methodological synergy? Combining critical discourse analysis and corpus linguistics to examine discourses of refugees and asylum seekers in the UK press. Discourse & Society 19(3): 273–306. DOI logoGoogle Scholar
Berry, Michael W., Dumais, Susan T. & O’Brien, Gavin
1995 Using linear algebra for intelligent information retrieval. SIAM Review 37(4): 573–595. [URL]. DOI logoGoogle Scholar
Biber, Douglas, Johansson, Stig, Leech, Geoffrey, Conrad, Susan & Finegan, Edward
1999 Longman Grammar of Spoken and Written English. London: Longman.Google Scholar
Blei, David M., Ng, Andrew Y. & Jordan, Michael I.
2003 Latent Dirichlet allocation. Journal of machine Learning Research 3: 993–1022. [URL]Google Scholar
Brezina, Vaclav, McEnery, Tony & Wattam, Stephen
2015 Collocations in context: A new perspective on collocation networks. International Journal of Corpus Linguistics 20(2): 139–173. DOI logoGoogle Scholar
Church, Kenneth W. & Hanks, Patrick
1990 Word association norms, mutual information, and lexicography. Computational Linguistics 16(1):22–29.Google Scholar
Davies, Mark
2012 Expanding horizons in historical linguistics with the 400-million word Corpus of Historical American English. Corpora 7(2): 121–157. [URL]. DOI logoGoogle Scholar
Didakowski, Jörg & Geyken, Alexander
2003 From DWDS corpora to a German word profile – methodological problems and solutions. In Network Strategies, Access Structures and Automatic Extraction of Lexicographical Information [OPAL X], Andrea Abel & Lothar Lemnitzer (eds). Mannheim: IDS. [URL]Google Scholar
Duff, Iain S., Grimes, Roger G. & Lewis, John G.
1989 Sparse matrix test problems. ACM Transactions on Mathematical Software (TOMS), 15(1): 1–14. DOI logoGoogle Scholar
Evert, Stefan
2005 The Statistics of Word Cooccurrences: Word Pairs and Collocations. PhD dissertation, University of Stuttgart. [URL]
2008 Corpora and collocations. In Corpus Linguistics. An International Handbook, Anke Lüdeling & Merja Kytö (eds), 1212–1248. Berlin: Mouton de Gruyter.Google Scholar
Fielding, Roy T.
2000 Architectural styles and the design of network-based software architectures. PhD dissertation, University of California, Irvine. [URL]Google Scholar
Firth, John Rupert
1957 Papers in Linguistics 1934–1951. London: OUP.Google Scholar
Gabrielatos, Costas, McEnery, Tony, Diggle, Peter J. & Baker, Paul
2012 The peaks and troughs of corpus-based contextual analysis. International Journal of Corpus Linguistics 17(2):151–175. DOI logoGoogle Scholar
Galbraith, Mary
1995 Deictic shift theory and the poetics of involvement in narrative. In Deixis in Narrative: A Cognitive Science Perspective, Judith F. Duchan, Gail A. Bruder & Lynne E. Hewitt (eds), 19–59. Hillsdale NJ: Lawrence Erlbaum Associates.Google Scholar
Geyken, Alexander
2013 Wege zu einem historischen Referenzkorpus des Deutschen: Das Projekt Deutsches Textarchiv. In Perspektiven einer corpusbasierten historischen Linguistik und Philologie [Thesaurus Linguae Aegyptiae 4], Ingelore Hafemann (eds), 221–234. Berlin: Berlin-Brandenburgische Akademie der Wissenschaften. [URL]Google Scholar
Geyken, Alexander, Barbaresi, Adrien, Didakowski, Jörg, Jurish, Bryan, Wiegand, Frank & Lemnitzer, Lothar
2017 Die Korpusplattform des “Digitalen Wörterbuchs der deutschen Sprache” (dwds). Zeitschrift für Germanistische Linguistik 45(2): 327–344. DOI logoGoogle Scholar
Glazebrook, Karl & Economou, Frossie
1997 PDL: The Perl data language. Dr. Dobb’s Journal, September 1997 <[URL]Google Scholar
Gries, Stephan Th. & Hilpert, Martin
2008 The identification of stages in diachronic data: Variability-based neighbor clustering. Corpora 3(1): 59–81. [URL]. DOI logoGoogle Scholar
Gulordava, Kristina & Baroni, Marco
2011 A distributional similarity approach to the detection of semantic change in the Google Books Ngram corpus. In Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics , Edinburgh, UK, July 2011, 67–71. Stroudsburg PA: ACL. [URL]
Heaps, H. Stanley
1978 Information Retrieval: Computational and Theoretical Aspects. Orlando FL: Academic Press.Google Scholar
Heidegger, Martin
1927 Sein und Zeit. In Jahrbuch für Philosophie und phänomenologische Forschung, Edmund Husserl (ed.). Tübingen: Neomarius.Google Scholar
Herrmann, J. Bernike
2013 Metaphor in Academic Discourse [LOT Dissertation Series]. Utrecht: Netherlands Graduate School of Linguistics.Google Scholar
Jurish, Bryan
2015 DiaCollo: On the trail of diachronic collocations. In CLARIN Annual Conference 2015 , Wrocław, Poland, October 14–16 2015, 28–31. [URL]
Jurish, Bryan, Thomas, Christian & Wiegand, Frank
2014 Querying the deutsches Textarchiv. In Proceedings of the Workshop “Beyond Single-Shot Text Queries: Bridging the Gap(s) between Research Communities” (MindTheGap 2014), Berlin, Germany, March 2014, Udo Kruschwitz, Frank Hopfgartner & Cathal Gurrin (eds), 25–30. [URL]Google Scholar
Jurish, Bryan, Geyken, Alexander & Werneke, Thomas
2016 DiaCollo: Diachronen Kollokationen auf der Spur. In Proceedings DHd 2016: Modellierung – Vernetzung – Visualisierung, University of Leipzig , March 2016, 172–175. [URL]
Kilgarriff, Adam & Tugwell, David
2002 Sketching words. In Lexicography and Natural Language Processing: A Festschrift in Honour of B. T. S. Atkins, Marie-Hélène Corréard (ed.), 125–137. [URL]Google Scholar
Kilgarriff, Adam, Herman, Andrej, Busta, Jan, Rychlý, Pavel & Jakubíček, Milos
2015 DIACRAN: A framework for diachronic analysis. In Proceedings of Corpus Linguistics 2015, Federica Formato & Andrew Hardie (eds), 65–70. Lancaster: UCREL.Google Scholar
Kim, Yoon, Chiu, Yi-K, Hanaki, Kentaro, Hegde, Darshan & Petrov, Slav
2014 Temporal analysis of language through neural language models. In Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science , June 2014, 61–65. Stroudsburg PA: ACL. [URL]. DOI logo
Manning, Christopher D. & Schütze, Hinrich
1999 Foundations of Statistical Natural Language Processing. Cambridge MA: The MIT Press.Google Scholar
Mikolov, Tomas, Chen, Kai, Corrado, Greg & Dean, Jeffrey
2013 Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781. [URL]
Moretti, Franco
2013 Distant Reading. London: Verso Books.Google Scholar
Rychlý, Pavel
2008 A lexicographer-friendly association score. In Proceedings of Recent Advances in Slavonic Natural Language Processing , RASLAN 2008, 6–9. [URL]
Sagi, Eyal, Kaufmann, Stefan & Clark, Brady
2009 Semantic density analysis: Comparing word meaning across time and phonetic space. In Proceedings of the EACL 2009 Workshop on Geometrical Models of Natural Language Semantics , March 2009. Stroudsburg PA: ACL. [URL]DOI logo
Scharloth, Joachim, Eugster, David & Bubenhofer, Noah
2013 Das Wuchern der Rhizome. Linguistische Diskursanalyse und Data-driven Turn. In Linguistische Diskursanalyse. Neue Perspektiven, Dietrich Busse & Wolfgang Teubert (eds), 345–380. Wiesbaden: VS Verlag. DOI logoGoogle Scholar
Schiller, Anne, Teufel, Simone & Thielen, Christine
1995 Guidelines fur das Tagging deutscher Textcorpora mit STTS. Technical report, University of Stuttgart, Institut für maschinelle Sprachverarbeitung and University of Tübingen, Seminar für Sprachwissenschaft.
Sokirko, A.
2003 A technical overview of DWDS/Dialing Concordance. Talk delivered at the meeting Computational Linguistics and Intellectual Technologies , Protvino, Russia. [URL]
Stalnaker, Robert C.
1974 Pragmatic presuppositions. In Semantics and Philosophy, Milton K. Munitz & Peter K. Unger (eds), 197–213. New York NY: New York University Press.Google Scholar
2002 Common ground. Linguistics and Philosophy 25(5): 701–721. DOI logoGoogle Scholar
Wang, Xuerui & McCallum, Andrew
2006 Topics over time: A non-Markov continuous-time model of topical trends. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’06, New York , 424–433. ACM. DOI logo
Cited by

Cited by 1 other publications

Bizzoni, Yuri, Stefania Degaetano-Ortlieb, Peter Fankhauser & Elke Teich
2020. Linguistic Variation and Change in 250 Years of English Scientific Writing: A Data-Driven Approach. Frontiers in Artificial Intelligence 3 DOI logo

This list is based on CrossRef data as of 8 march 2023. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.