[PLing] Guest lecture by Axel Bohmann (Uni Freiburg): Adventures in Multi-dimensional Analysis

[Andreas Baumann]

Dear colleagues,


you are cordially invited to a guest lecture by the Dr. Axel Bohmann, socio-linguist at the University of Freiburg (English Seminar), on "Adventures in Multi-dimensional Analysis".


It will take place on Wednesday, 16.11.2022, 11:30-13:00, BIG Hörsaal (Hauptgebäude, Audimax-Passage) as part of the lecture "Quantitative Methoden in den Digital Humanities"<https://ufind.univie.ac.at/de/course.html?lv=136101&semester=2022W>. The abstract can be found below.


Best regards,

Andreas Baumann



Adventures in Multi-dimensional Analysis



Linguistic variation and change do not occur in a vacuum, but are always embedded in specific (written or oral) texts. Such texts contain a wide range of linguistic features, which themselves are related to each other in non-random, functionally interpretable ways. Based on these two observations, the method of multi-dimensional analysis (MDA; Biber 1988) proposes to analyze textual relations through consideration of the covariance of many individual linguistic features. The fact, for instance, that the passive voice tends to occur at relatively higher frequencies in texts which also contain high frequencies of nominalizations but comparatively low frequencies of personal pronouns, marks all three features as related to each other in a specific way. MDA employs exploratory factor analysis (Gorsuch 2015) to describe such relations among features in interpretable ways, allowing description of different feature combinations as functionally motivated dimensions of variation.

            The present talk gives a non-technical introduction to MDA and highlights its potential through a number of case studies. First, an MDA of ten corpora in the International Corpus of English (ICE; Greenbaum & Nelson 1996) suite is used to establish dimensions of variation in English worldwide and test the importance of genre and geography in structuring this variation. Next, the predictive power of the established dimensions of variation for analyses of further features is demonstrated on the basis of variable verb complementation with gerunds versus to-infinitives. Finally, the MDA method is applied to a large corpus of relatively unstructured data, the Corpus of Global Web-based English (GloWbE; Davies & Fuchs 2015), in order to better understand genre variation in the absence of detailed text category labeling.



References:

Biber, Douglas. 1988. Variation across Speech and Writing. Cambridge, New York: Cambridge University Press.

Davies, Mark & Robert Fuchs. 2015. Expanding horizons in the study of World Englishes with the 1.9 billion word Global Web-based English Corpus (GloWbE). English World-Wide 36(1). 1–28.

Gorsuch, Richard L. 2015. Factor analysis. Classic edition. New York; London: Routledge.

Greenbaum, Sidney & Gerald Nelson. 1996. The International Corpus of English (ICE) project. World Englishes 15(1). 3–15.




__________________

MMag. Dr. Andreas Baumann
Senior Scientist
Coordinator Digital Humanities/Philology
Department of European and Comparative Literature and Language Studies
University of Vienna
Universitätsring 1, Hauptgebäude, Stiege 8, 2. Stock
1010 Wien

Email: andreas.baumann at univie.ac.at
Phone: +43 1 4277 43062
Zoom: https://univienna.zoom.us/j/9782332000
https://evsl.univie.ac.at/digital-philology/baumann/

Baumann, A.; Mühlenbernd, R. 2022. Less of the same: modeling horror aequi and extravagance as mechanisms of negative frequency dependence in linguistic diversification. Proc. Joint Conference on Language Evolution. https://phaidra.univie.ac.at/o:1590491
Kolb, T. E.; Sekanina, K.; Kern, B. M.; Neidhardt, J.; Wissik, T.; Baumann, A. 2022. The ALPIN Sentiment Dictionary: Austrian Language Polarity in Newspapers. Proc. 13th Conference on Language Resources and Evaluation (LREC 2022): 4708–4716.
Kern, B.; Baumann, A.; Kolb, T.; Sekanina, K.; Neidhardt, J. 2021. A review and cluster analysis of German polarity resources for sentiment analysis. Proc. 3rd Conference on Language, Data and Knowledge. 37:1--37:17.

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