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Dr Martin Schweinberger
Dr

Martin Schweinberger

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+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

94 works between 2008 and 2025

41 - 60 of 94 works

2021

Journal Article

Voices from the periphery: perceptions of Indonesian primary vs secondary pre-service teacher trainees about corpora and data-driven learning in the L2 English classroom

Crosthwaite, Peter, Luciana and Schweinberger, Martin (2021). Voices from the periphery: perceptions of Indonesian primary vs secondary pre-service teacher trainees about corpora and data-driven learning in the L2 English classroom. Applied Corpus Linguistics, 1 (1) 100003, 1-13. doi: 10.1016/j.acorp.2021.100003

Voices from the periphery: perceptions of Indonesian primary vs secondary pre-service teacher trainees about corpora and data-driven learning in the L2 English classroom

2021

Other Outputs

Fixed- and mixed-effects regression models in R

Schweinberger, Martin (2021). Fixed- and mixed-effects regression models in R. Brisbane, QLD, Australia: The University of Queensland, School of Languages and Cultures.

Fixed- and mixed-effects regression models in R

2021

Journal Article

Analysing discourse around COVID-19 in the Australian Twittersphere: a real-time corpus-based analysis

Schweinberger, Martin, Haugh, Michael and Hames, Sam (2021). Analysing discourse around COVID-19 in the Australian Twittersphere: a real-time corpus-based analysis. Big Data and Society, 8 (1), 205395172110214. doi: 10.1177/20539517211021437

Analysing discourse around COVID-19 in the Australian Twittersphere: a real-time corpus-based analysis

2021

Book Chapter

Using intensifier-adjective collocations to investigate mechanisms of change

Schweinberger, Martin (2021). Using intensifier-adjective collocations to investigate mechanisms of change. Variation in time and space: observing the world through corpora. (pp. 231-255) edited by Anna Čermáková and Markéta Malá. Berlin, Germany: De Gruyter. doi: 10.1515/9783110604719-010

Using intensifier-adjective collocations to investigate mechanisms of change

2021

Other Outputs

Tree-based models in R

Schweinberger, Martin (2021). Tree-based models in R. Brisbane, QLD, Australia: The University of Queensland, School of Languages and Cultures.

Tree-based models in R

2021

Book Chapter

On the waning of forms – a corpus-based analysis of decline and loss in adjective amplification

Schweinberger, Martin (2021). On the waning of forms – a corpus-based analysis of decline and loss in adjective amplification. Lost in change: causes and processes in the loss of grammatical elements and constructions. (pp. 235-260) edited by Svenja Kranich and Tine Breban . Amsterdam, Netherlands: John Benjamins Publishing Company. doi: 10.1075/slcs.218.08sch

On the waning of forms – a corpus-based analysis of decline and loss in adjective amplification

2021

Journal Article

Analyzing Historical Changes in the Irish English Amplifier System

Schweinberger, M. (2021). Analyzing Historical Changes in the Irish English Amplifier System. Anglistik, 32 (1), 139-158. doi: 10.33675/angl/2021/1/11

Analyzing Historical Changes in the Irish English Amplifier System

2020

Journal Article

A corpus-based analysis of differences in the use of very for adjective amplification among native speakers and learners of English

Schweinberger, Martin (2020). A corpus-based analysis of differences in the use of very for adjective amplification among native speakers and learners of English. International Journal of Learner Corpus Research, 6 (2), 163-192. doi: 10.1075/ijlcr.20011.sch

A corpus-based analysis of differences in the use of very for adjective amplification among native speakers and learners of English

2020

Journal Article

Less is more? The impact of written corrective feedback on corpus-assisted L2 error resolution

Crosthwaite, Peter, Storch, Neomy and Schweinberger, Martin (2020). Less is more? The impact of written corrective feedback on corpus-assisted L2 error resolution. Journal of Second Language Writing, 49 100729, 100729. doi: 10.1016/j.jslw.2020.100729

Less is more? The impact of written corrective feedback on corpus-assisted L2 error resolution

2020

Journal Article

How learner corpus-research can inform language learning and teaching

Schweinberger, Martin (2020). How learner corpus-research can inform language learning and teaching. Australian Review of Applied Linguistics, 43 (2), 195-217.

How learner corpus-research can inform language learning and teaching

2020

Journal Article

How learner corpus research can inform language learning and teaching: an analysis of adjective amplification among L1 and L2 English speakers

Schweinberger, Martin (2020). How learner corpus research can inform language learning and teaching: an analysis of adjective amplification among L1 and L2 English speakers. Australian Review of Applied Linguistics, 43 (2), 196-218. doi: 10.1075/aral.00032.sch

How learner corpus research can inform language learning and teaching: an analysis of adjective amplification among L1 and L2 English speakers

2020

Journal Article

Speech-unit final like in Irish English

Schweinberger, Martin (2020). Speech-unit final like in Irish English. English World-Wide, 41 (1), 89-117. doi: 10.1075/eww.00041.sch

Speech-unit final like in Irish English

2020

Book Chapter

Analyzing change in the American English amplifier system in the fiction genre

Schweinberger, Martin (2020). Analyzing change in the American English amplifier system in the fiction genre. Corpora and the changing society: studies in the evolution of English. (pp. 223-249) edited by Paula Rautionaho, Arja Nurmi and Juhani Klemola. Amsterdam, Netherlands: John Benjamins Publishing Company. doi: 10.1075/scl.96.09sch

Analyzing change in the American English amplifier system in the fiction genre

2020

Conference Publication

Using Semantic Vector Space Models to investigate lexical replacement – a corpus based study of ongoing changes in intensifier systems

Schweinberger, Martin (2020). Using Semantic Vector Space Models to investigate lexical replacement – a corpus based study of ongoing changes in intensifier systems. Methods in Dialectology XVI, Tachikawa, Japan, 7 - 11 August 2017. Berlin, Germany: Peter Lang. doi: 10.3726/b17102

Using Semantic Vector Space Models to investigate lexical replacement – a corpus based study of ongoing changes in intensifier systems

2019

Journal Article

A sociolinguistic analysis of emotives

Schweinberger, Martin (2019). A sociolinguistic analysis of emotives. Corpus Pragmatics, 3 (4), 327-361. doi: 10.1007/s41701-019-00062-z

A sociolinguistic analysis of emotives

2019

Other Outputs

The Language Technology and Data Analysis Laboratory (LADAL)

Schweinberger, Martin (2019). The Language Technology and Data Analysis Laboratory (LADAL). Brisbane, QLD, Australia: The University of Queensland, School of Languages and Cultures.

The Language Technology and Data Analysis Laboratory (LADAL)

2018

Conference Publication

A corpus-based analysis of the L1-acquisition of amplifiers in American English

Schweinberger, Martin (2018). A corpus-based analysis of the L1-acquisition of amplifiers in American English. 5th International Conference of the International Society for the Linguistics of English (ISLE 5), London, United Kingdom, 17-20 July 2018.

A corpus-based analysis of the L1-acquisition of amplifiers in American English

2018

Journal Article

The discourse particle eh in New Zealand English

Schweinberger, Martin (2018). The discourse particle eh in New Zealand English. Australian Journal of Linguistics, 38 (3), 395-420. doi: 10.1080/07268602.2018.1470458

The discourse particle eh in New Zealand English

2018

Journal Article

Swearing in Irish English: a corpus-based quantitative analysis of the sociolinguistics of swearing

Schweinberger, Martin (2018). Swearing in Irish English: a corpus-based quantitative analysis of the sociolinguistics of swearing. Lingua, 209, 1-20. doi: 10.1016/j.lingua.2018.03.008

Swearing in Irish English: a corpus-based quantitative analysis of the sociolinguistics of swearing

2018

Conference Publication

Analyzing diachronic change in the American English amplifier system

Schweinberger, Martin (2018). Analyzing diachronic change in the American English amplifier system. ICAME 39 (39th Meeting of the International Computer Archive of Modern and Medieval English), Tampere, Finland, 30 May - 3 June 2018.

Analyzing diachronic change in the American English amplifier system

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

Looking for a supervisor? Read our advice on how to choose 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

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

    Associate Advisor

    Other advisors: Associate Professor Peter Crosthwaite

  • Doctor Philosophy

    Enhancing Lexical Resources for Argumentative Essay Writing through Corpus Integration

    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

  • Doctor Philosophy

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

    Associate Advisor

    Other advisors: Associate Professor Peter Crosthwaite

Completed supervision

Media

Enquiries

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