List of John Benjamins publications for which Martin Schweinberger plays a role.
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: Online-First Articles2022.
This paper uses a bibliometric analysis to map the field of Corpus Linguistics (CL) research in arts and humanities over the last 20 years, tracking changes in popular CL research topics, outlets, highly cited authors, and geographical origins based on the metadata of 5,829 CL-related articles… read more | Article
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, Kranich, Svenja and Tine Breban (eds.), pp. 235–2602021.
This study takes a corpus-based approach to investigating the decline and near-loss of very as an adjective amplifier in spoken New Zealand English (NZE) based on The Wellington Corpus of Spoken New Zealand English. The paper analyzes the replacement of very as the dominant adjective amplifier… read more | Chapter
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, pp. 163–1922020.
This paper analyzes the use of very as an adjective amplifier by native speakers and advanced learners of English with diverse language backgrounds based on the International Corpus of Learner English (ICLE) and the Louvain Corpus of Native English Essays (LOCNESS). The study applies Multifactorial… read more | Article
This paper investigates the use of speech-unit final like (SUF like) in standard Irish English (IrE) and takes a variationist approach based on the Irish component of the International Corpus of English (ICE-IRL). The analysis includes both sociolinguistic factors (age, gender, occupation type,… read more | Article
How Learner Corpus Research can inform language learning and teaching: An analysis of adjective amplification among L1 and L2 English speakers. Corpus Linguistics and Education in Australia, García, Alexandra I., Peter Crosthwaite and Monika Bednarek (eds.), pp. 196–2182020.
This study aims to exemplify how language teaching can benefit from learner corpus research (LCR). To this end, this study determines how L1 and L2 English speakers with diverse L1 backgrounds differ with respect to adjective amplification, based on the International Corpus of Learner English… read more | Article
Analyzing change in the American English amplifier system in the fiction genre. Corpora and the Changing Society: Studies in the evolution of English, Rautionaho, Paula, Arja Nurmi and Juhani Klemola (eds.), pp. 223–2502020.
This study examines the diachronic development of amplification of adjectives in American English (AmE), specifically in the fiction section of the Corpus of Historical American English (COHA). The results show that amplifier use in attributive contexts remains stable, while, in predicative… read more | Chapter
A comparative study of the pragmatic marker like in Irish English and in south-eastern varieties of British English. Pragmatic Markers in Irish English, Amador-Moreno, Carolina P., Kevin McCafferty and Elaine Vaughan (eds.), pp. 114–1342015.
This study compares the use of like in Irish English (IrE) to its use in southeastern British English (SE-BrE). There are significant differences between the use of like in IrE and SE-BrE in terms of overall frequency, social meaning and positioning. This paper argues that the differences in the… read more | Article
The discourse marker LIKE in Irish English. New Perspectives on Irish English, Migge, Bettina and Máire Ní Chiosáin (eds.), pp. 179–2022012.
This paper analyses the use of the discourse marker LIKE in Irish English (IrE) with respect to a speaker’s age and gender and illustrates how the International Corpus of English (ICE) can be used for fine-grained sociolinguistic analyses. The results suggest that LIKE use significantly decreases… read more | Article