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Dr Martin Schweinberger
Dr

Martin Schweinberger

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Phone: 
+61 7 336 56892

Overview

Background

Martin Schweinberger uses big data and computational methods to explore the messy, fascinating reality of how people actually talk—including all the swear words, filler words, and informal expressions that traditional language education overlooks. As a Lecturer in Applied Linguistics at the University of Queensland, he bridges the gap between computer science and linguistics to understand how language evolves in our digital age.

Uncovering Hidden Language Patterns

Much of Martin's research focuses on the language phenomena that schools don't teach but that permeate everyday conversation. He analyzes massive datasets to study vulgarity and swearing patterns, as well as discourse markers—those ubiquitous filler words like "like," "you know," "well," and "I mean" that pepper our speech. By applying statistical methods to real-world language use, he reveals how these supposedly "incorrect" forms of expression actually follow sophisticated social and linguistic rules.

His work also tracks how language changes over time and varies between different social settings, using computational tools to identify patterns that would be impossible to detect through traditional research methods alone.

Building Australia's Language Data Future

As Director of the Language Technology and Data Analysis Laboratory (LADAL)—a free upskilling platform for language data science with hundreds of thousands of users worldwide—and a key figure in one of Australia's major research infrastructure projects, the Language Data Commons of Australia (LDaCA), Martin is helping build the digital infrastructure that will support language research across the country. LDaCA has received substantial funding to create accessible tools and resources that allow researchers to analyze text and speech data more effectively.

Championing Research Transparency

Beyond his linguistic research, Martin advocates for reproducibility and transparency in humanities and social science research. He provides guidance on how language researchers can adopt more rigorous, open research practices—addressing a growing concern about the reliability of academic findings across disciplines.

Martin's international visibility is reflected in his leadership roles: he serves as Vice-President Professional of the International Society for the Linguistics of English (ISLE) and sits on the board of The International Computer Archive of Modern and Medieval English (ICAME), one of the oldest and most reputable societies for corpus linguistics. These positions demonstrate his commitment to advancing computational language research on a global scale.

Potential topics for supervision

I would be particularly interested in supervising theses on the following topics:

Sociolinguistics / Language Variation and Change / World Englishes

  • General extenders
  • Terms-of-address and salutations
  • Discourse particles and markers
  • Vulgarity
  • Adjective amplification

Learner Language / Applied Linguistics / Corpus Phonetics / Learner Corpus Research

  • Vowel production among L1 speakers and learners of English
  • Voice-onset-times among L1 speakers and learners of English
  • Fluency and pauses in learner and L1 speech.
  • Accent and intelligibility / comprehension.

Text Analytics / Digital Humanities / Corpus Linguistics

  • Applied word embedding applications in the language sciences.
  • Comparison of different association / keyness measures

Availability

Dr Martin Schweinberger is:
Available for supervision
Media expert

Qualifications

  • Doctor of Philosophy, Universität Hamburg

Research interests

  • Vulgarity and Swearing

    I investigate how swear words and taboo language are used in everyday speech and online discourse. Contrary to popular belief, vulgar language follows systematic social and linguistic rules. My research uncovers how such expressions function in communication and what they reveal about speakers’ identities, emotions, and group memberships.

  • Discourse Markers and Filler Words

    I study words like like, you know, and well—terms often dismissed as meaningless. Using computational analysis, I show how these elements structure conversations and convey nuanced meanings. My work demonstrates that such "filler" words play important roles in signaling attitudes, managing interactions, and guiding listener expectations.

  • Open Science and Research Transparency

    I actively promote reproducible, open research practices in the humanities and social sciences. I provide practical training and resources to help language researchers adopt transparent workflows. My advocacy supports greater academic rigor and long-term trust in empirical research.

  • Text Analytics and Computational Linguistics

    I apply computational methods—like machine learning and statistical modelling—to large corpora to uncover hidden linguistic patterns. These tools help quantify language use in a way that supports replicable, empirical research. My work is at the intersection of computer science and linguistics, making it especially relevant in the digital age.

  • Digital Infrastructure and Research Tools

    As Director of LADAL and a lead in LDaCA, I am building accessible digital platforms that support large-scale language analysis. These initiatives democratize access to language data and computational tools for researchers, students, and educators alike. My infrastructure work enhances the capacity for advanced language research in Australia and beyond.

  • Language Variation and Change

    I explore how language evolves over time and across different social settings. By analyzing large-scale linguistic datasets, I identify subtle patterns of variation in how people speak, particularly in informal and digital contexts. This research helps reveal how social norms and technology influence the way we communicate.

  • Learner Language and Second Language Acquisition

    I analyze how learners of English produce sounds, manage fluency, and develop pronunciation over time. This includes examining features like vowel quality, voice-onset time, pauses, and accent intelligibility. By comparing learner and native speaker data, my research informs language teaching and helps improve learner outcomes.

  • Corpus Phonetics

    I use corpus-based methods to investigate the phonetic characteristics of spoken language, including pronunciation patterns among both native and non-native speakers. I focus on measurable acoustic features such as vowel production and timing cues. This approach allows for the large-scale, data-driven analysis of speech in real-life settings.

Research impacts

As director and initiator of the Language Technology and Data Analysis Laboratory (LADAL) I am very proud that LADAL has emerged as one of Australia’s most prominent web-based collaborative support infrastructures for digital and computational humanities with more than 1.1 million page views of more than 500,000 active users in nearly 750,000 engaged sessions since 2021.

Works

Search Professor Martin Schweinberger’s works on UQ eSpace

89 works between 2008 and 2025

1 - 20 of 89 works

2025

Journal Article

Vulgarity in online discourse around the English-speaking world

Schweinberger, Martin and Burridge, Kate (2025). Vulgarity in online discourse around the English-speaking world. Lingua, 321 103946, 1-25. doi: 10.1016/j.lingua.2025.103946

Vulgarity in online discourse around the English-speaking world

2025

Other Outputs

Indigenous Australian languages – linguistic features, revitalization efforts, and research infrastructure for archiving and accessibility

Schweinberger, Martin (2025). Indigenous Australian languages – linguistic features, revitalization efforts, and research infrastructure for archiving and accessibility. Hamburg, Germany: University of Hamburg.

Indigenous Australian languages – linguistic features, revitalization efforts, and research infrastructure for archiving and accessibility

2024

Journal Article

Seeded topic modeling as a more appropriate alternative to unsupervised standard topic models

Schweinberger, Martin (2024). Seeded topic modeling as a more appropriate alternative to unsupervised standard topic models. Discourse Studies. doi: 10.1177/14614456241293895

Seeded topic modeling as a more appropriate alternative to unsupervised standard topic models

2024

Other Outputs

Vulgarity in online discourse around the English-speaking world

Schweinberger, Martin (2024). Vulgarity in online discourse around the English-speaking world. Bonn, Germany: University of Bonn.

Vulgarity in online discourse around the English-speaking world

2024

Book Chapter

A corpus-based comparative acoustic analysis of target-like vowel production by L1-Japanese learners and native speakers of English

Schweinberger, Martin and Komiya, Yuki (2024). A corpus-based comparative acoustic analysis of target-like vowel production by L1-Japanese learners and native speakers of English. Crossing Boundaries through Corpora: Innovative corpus approaches within and beyond linguistics. (pp. 41-61) edited by Sarah Buschfeld, Patricia Ronan, Theresa Neumaier, Andreas Weilinghoff and Lisa Westermayer. Amsterdam, Netherlands: John Benjamins Publishing Company. doi: 10.1075/scl.119.03sch

A corpus-based comparative acoustic analysis of target-like vowel production by L1-Japanese learners and native speakers of English

2024

Book Chapter

An introduction to sociopragmatic variation

Ronan, Patricia and Schweinberger, Martin (2024). An introduction to sociopragmatic variation. Socio-Pragmatic Variation in Ireland. (pp. 1-8) Berlin, Germany: De Gruyter. doi: 10.1515/9783110791457-001

An introduction to sociopragmatic variation

2024

Book Chapter

Concluding remarks and future directions in studies on sociopragmatic variation

Schweinberger, Martin and Ronan, Patricia (2024). Concluding remarks and future directions in studies on sociopragmatic variation. Socio-pragmatic variation in Ireland: using pragmatic variation to construct social identities. (pp. 235-240) edited by Martin Schweinberger and Patricia Ronan. Berlin, Germany: De Gruyter Mouton. doi: 10.1515/9783110791457-012

Concluding remarks and future directions in studies on sociopragmatic variation

2024

Book Chapter

Boring much? Semantic determinants of constructional attraction in Irish English

Schweinberger, Martin and Ronan, Patricia (2024). Boring much? Semantic determinants of constructional attraction in Irish English. Socio-Pragmatic Variation in Ireland. (pp. 107-130) Berlin, Germany: De Gruyter. doi: 10.1515/9783110791457-007

Boring much? Semantic determinants of constructional attraction in Irish English

2024

Conference Publication

Automated, Corpus-and Usage-Based Semantic Classification of Word Class using Word Embeddings

Schweinberger, Martin and Luo, Chang-Hao (2024). Automated, Corpus-and Usage-Based Semantic Classification of Word Class using Word Embeddings. ICAME45, Vigo, Spain, 18-21 June 2024.

Automated, Corpus-and Usage-Based Semantic Classification of Word Class using Word Embeddings

2024

Other Outputs

Introduction to R for Social Science

Schweinberger, Martin (2024). Introduction to R for Social Science. Joensuu, Finland: University of Eastern Finland.

Introduction to R for Social Science

2024

Other Outputs

Introduction to Computational Text Analytics (Workshop)

Schweinberger, Martin and Hames, Sam (2024). Introduction to Computational Text Analytics (Workshop). Brisbane, QLD Australia: The University of Queensland.

Introduction to Computational Text Analytics (Workshop)

2024

Journal Article

Corpus-based discourse analysis: from meta-reflection to accountability

Bednarek, Monika, Schweinberger, Martin and Lee, Kelvin K. H. (2024). Corpus-based discourse analysis: from meta-reflection to accountability. Corpus Linguistics and Linguistic Theory, 20 (3), 1-28. doi: 10.1515/cllt-2023-0104

Corpus-based discourse analysis: from meta-reflection to accountability

2024

Journal Article

A corpus‐based analysis of adjective amplification in Hong Kong, Indian and Philippine English

Schweinberger, Martin (2024). A corpus‐based analysis of adjective amplification in Hong Kong, Indian and Philippine English. World Englishes. doi: 10.1111/weng.12640

A corpus‐based analysis of adjective amplification in Hong Kong, Indian and Philippine English

2024

Book Chapter

When natural language processing meets corpus linguistics

Schweinberger, Martin (2024). When natural language processing meets corpus linguistics. Digitally-assisted historical English linguistics. (pp. 73-88) edited by Carolina P. Amador-Moreno, Dagmar Haumann and Arne Peters. New York, NY, United States: Routledge. doi: 10.4324/9781003360285-6

When natural language processing meets corpus linguistics

2023

Other Outputs

Introduction to Dimension Reduction Methods with R

Schweinberger, Martin (2023). Introduction to Dimension Reduction Methods with R. Tromsø, Norway: The Arctic University of Norway.

Introduction to Dimension Reduction Methods with R

2023

Journal Article

On the L1-acquisition of the pragmatics of discourse like

Schweinberger, Martin (2023). On the L1-acquisition of the pragmatics of discourse like. Functions of Language, 30 (3), 255-286. doi: 10.1075/fol.20025.sch

On the L1-acquisition of the pragmatics of discourse like

2023

Other Outputs

F%$# Twitter. A corpus-based analysis of vulgar language on Twitter

Schweinberger, Martin (2023). F%$# Twitter. A corpus-based analysis of vulgar language on Twitter. Bayreuth, Germany: Bayreuth University.

F%$# Twitter. A corpus-based analysis of vulgar language on Twitter

2023

Journal Article

Research trends in corpus linguistics: a bibliometric analysis of two decades of Scopus-indexed corpus linguistics research in arts and humanities

Crosthwaite, Peter, Ningrum, Sulistya and Schweinberger, Martin (2023). Research trends in corpus linguistics: a bibliometric analysis of two decades of Scopus-indexed corpus linguistics research in arts and humanities. International Journal of Corpus Linguistics, 28 (3), 344-377. doi: 10.1075/ijcl.21072.cro

Research trends in corpus linguistics: a bibliometric analysis of two decades of Scopus-indexed corpus linguistics research in arts and humanities

2023

Conference Publication

An introduction to the resources provided by LADAL - the Language Technology and Data Analysis Laboratory

Schweinberger, Martin (2023). An introduction to the resources provided by LADAL - the Language Technology and Data Analysis Laboratory. 7th Meeting of the International Society for the Linguistics of English (ISLE7), Brisbane, QLD, Australia, 19 - 23 June 2023. Brisbane, QLD, Australia: University of Queensland.

An introduction to the resources provided by LADAL - the Language Technology and Data Analysis Laboratory

2023

Conference Publication

Who swears most – and in what social settings?

Schweinberger, Martin, Fatemi, Masoud, Hames, Sam, Haugh, Michael, Laitinen, Mikko, Rautionaho, Paula and Takahashi, Marissa (2023). Who swears most – and in what social settings?. 7th Meeting of the International Society for the Linguistics of English (ISLE7), Brisbane, QLD, Australia, 19-23 June 2023. Brisbane, QLD, Australia: University of Queensland.

Who swears most – and in what social settings?

Funding

Current funding

  • 2024 - 2028
    Language Data Commons of Australia (LDaCA-RDC)
    Australian Research Data Commons Limited
    Open grant

Past funding

  • 2021 - 2024
    Language Data Commons of Australia HASS RDC (LDaCA-RDC)
    ARDC - Australian Data Partnerships
    Open grant

Supervision

Availability

Dr Martin Schweinberger is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Supervision history

Current supervision

  • Doctor Philosophy

    A multifactorial study of morpho-syntactic errors across different L1 backgrounds and language proficiency levels

    Principal Advisor

    Other advisors: Associate Professor Peter Crosthwaite

  • Doctor Philosophy

    A corpus-based analysis of conspiracy theory discourse on Reddit: Understanding conspiracy-fuelled anomie and moral panics during COVID-19

    Principal Advisor

    Other advisors: Professor Ryan Ko

  • Doctor Philosophy

    Corpus-based investigation of three-minute thesis presentations: Register perspective

    Associate Advisor

    Other advisors: Associate Professor Peter Crosthwaite

  • Doctor Philosophy

    The Relationship Between Writing Tasks and Second Language Writers¿ Use of Metadiscourse

    Associate Advisor

    Other advisors: Associate Professor Peter Crosthwaite

  • Doctor Philosophy

    Integrating Artificial Intelligence and Machine Learning in TESOL: A Study on Personalised Learning and Impact on Student Engagement and Motivation in A Rural Indonesian University

    Associate Advisor

    Other advisors: Associate Professor Peter Crosthwaite

Completed supervision

Media

Enquiries

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