Methods in Morphological Research*
Workshop convenors: Pascual Cantos Gómez (University of Murcia), Ana Díaz-Negrillo (University of Granada), Salvador Valera (University of Granada)
The emphasis on methodological rigour appears to have gained prominence in linguistics in general, as evidenced by publications such as Enghels, Defrancq & Jansegers (2020) in Contrastive Linguistics, or Kessler (2026), and Klassen & Schwieter (2026) in Applied Linguistics, to cite some references from various fields. In the case of morphological research, methodological questions are addressed explicitly or implicitly in several references too, e.g. in Körtvélyessy (2020), Varvara, Salvadori & Huyghe (2022), or Huyghe & Varvara (2025), to name some. This workshop addresses three areas of interest for word-formation (but submissions on related fields are invited too):
Statistical analysis: Virtually every recent publication of interest based on quantitative data and published by frontline journals uses statistical analysis. Still, the choice of which statistical analysis in particular is used is often debated and remains a relatively frequent source of disagreement between authors and reviewers, whenever the choice is discussed. Despite specific publications on the issue, like Brezina (2018) or Gries (2023), the average linguist sometimes finds themselves lost in an area that they need for research but where they may not have enough specific knowledge. This workshop invites submissions on quantitative measures in general or on specific issues in word-formation research.
Data sources: Closely connected to the former, quantitative research typically relies on corpus data, even if specific fields fail to find enough evidence in the corpora widely available and turn to dictionary data. The (mis)match between corpus and dictionary data, the reliability of dictionary data in various regards, and the possibility of other data sources is a constant source of debate in word-formation research. Besides the well-known difficulties in the identification of certain types, like compounds or blends, how else can sufficient, reliable data be collected besides corpora and dictionaries?
Artificial Intelligence: The elephant in the room, or maybe not any more. AI has joined research on word-formation in unexpected ways, very much like spreadsheets or statistical packages did decades ago. The sooner we become familiar with them, the better it is for the quality of research, so how do we use AI for word-formation research? What do we need to know—the essentials and beyond? More important, which areas need what to join AI-assisted research?
Please submit anonymous abstracts of up to 300 words (excluding references) to Salvador Valera (svalera@ugr.es) by 15 March 2027.
References
Brezina, Vaclav. 2018. Statistics in Corpus Linguistics: A Practical Guide. Cambridge: Cambridge University Press.
Enghels, Renata, Bart Defrancq & Marlies Jansegers. 2020. New Approaches to Contrastive Linguistics: Empirical and Methodological Challenges. Berlin: de Gruyter.
Gries, Stefan Th. 2023. New technologies and advances in statistical analysis in recent decades. In Manuel Díaz-Campos & Sonia Balasch (eds.), The Handbook of Usage-Based Linguistics. Hoboken: John Wiley & Sons; 561-579.
Huyghe, Richard & Rossella Varvara. 2025. Semantic granularity in derivation. Linguistics Vanguard 11(1): 73-85.
Kessler, Matt. 2026. Digital and Internet-Based Research Methods in Applied Linguistics. Amsterdam: John Benjamins.
Klassen, Gabrielle & John W. Schwieter (eds.). 2026. Quantitative Methods in Multilingual Acquisition and Processing. Amsterdam: John Benjamins.
Körtvélyessy, Lívia. 2020. Onomatopoeia – A unique species? Studia Linguistica, 74: 506-551.
Varvara, Rossella, Justine Salvadori & Richard Huyghe. 2022. Annotating complex words to investigate the semantics of derivational processes. In Harry Bunt (ed.), Proceedings of ISA-18 Workshop at LREC2022. Marseille: European Language Resources Association; 133-141.
* Supported by research project PID2024-160050NB-I00, funded by the European Regional Development Fund (ERDF) and the State Research Agency (SRA) of the Spanish Ministry of Science and Innovation.