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Dr Martin Schweinberger

ABOUT

My name is Martin Schweinberger and I am Lecturer in Applied Linguistics at the University of Queensland (UQ) in Australia as well as a part-time Associate Professor at the Arctic University of Norway in Tromsø where I am the Principle Data Science Advisor to the AcqVA Aurora Lab in the Aurora Center for Language Acquisition, Variation, and Attrition (AcqVA). At the University of Queensland, I am Director of the Language Technology and Data Analysis Laboratory (LADAL) (together with Michael Haugh) and I would consider myself a quantitative corpus linguist specialized in computational analyses of text and speech. In my research, I aim to combine and bridge the gap between computational linguistics and corpus linguistics.

I am steering committee member and Chief Investigator (CI) of the Australian Text Analytics Platform (ATAP) where I focus on producing resources and training through LADAL. I am also CI and on the advisory committee of the Language Data Commons of Australia (LDaCA). Both ATAP and LDaCA aim at establishing  language data infrastructures and text analytics upskilling resources in Australia and they have received substantive funding from the Australian Research Data Commons (ARDC). I have recently been elected as Vice-President Profession to be of the International Society for the Linguistics of English (ISLE) and I am board member of The International Computer Archive of Modern and Medieval English (ICAME).

Regarding my background, I have a PhD in English linguistics and I studied at the National University of Ireland, Galway, and Universität Kassel where I graduated in 2008 with an MA in English Philology, Philosophy, and Psychology. After my MA, I remained in Kassel for a short while but soon moved to Hamburg where I worked on and later received my PhD.

RESEARCH AREAS

  • Mechanisms of language variation and change
  • Determinants of language use and linguistic variability
  • Discourse markers and particles / adjective intensi fication
  • L1 & L2 acquisition
  • Computational modelling and visualization of linguistic data
  • Computational Humanities (Digital Humanities)
  • Language Data Science and reproducibility
  • Best Practices in text analytics and data management

DIGITAL FOOTPRINT

My ORCID is 0000-0003-1923-9153 and you can also find me on ResearchGate, LinkedIn, Github, GitLab, or follow me on Twitter (@ronautic).

Martin Schweinberger

NEWS

16/1/2023: I’ll give a workshop on advanced dimension-reduction methods and using  online computing at the AcqVA Aurora Centre at UiT.

16/12/2023: I have been invited to give a talk at the University of Innsbruck. The talk is about what we can learn from analyses of adjective amplification (you can find the slides here).

13/12/2023: I’m invited to give a talk on my research about computational analyses of vowel production among L1- and L2-speakers of English at the Carl von Ossietzky University Oldenburg.

2/11/2023: I  just checked the web-traffic analytics of LADAL and since starting the analytics on January 1, 2021, we have had more than 750,000 page views, 400,000+ active sessions, and 300,000+ users! This is really fantastic and I’m really happy that so many people use LADAL resources and that it recives such a fantastic uptake.

19/1/2023: I am giving a workshop on conditional inference trees at the Rheinische Friedrich-Wilhelms-Universität Bonn (workshop materials).

13/1/2023: I am invited to give a talk entitled Reproducibility in corpus-based computational analyses of learner speech at the Institute of English Studies at the University of Hamburg (slides).

25/10/2022: I have the honour of giving a talk about transparency and reproducibility in Corpus Linguistics for the Sydney Corpus Lab led by Monika Bednarek at the University of Sydney. Here is a link to the slides.

1/9/2022: I co-organized the workshop Computational Thinking in the Humanities. The workshop focused on the history and future as well as the challenges and the potential of computational approaches in the humanities and social sciences with several showcases on what computation have to offer and can achieve in HASS research.

ACKNOWLEDGEMENTS

I would like to thank Susanne Flach for her help in setting up this website.

(last updated 2023/11/2)

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