The Current State and Prominent Features of Quantitative Linguistics Through the Lens of QUALICO 2023: A Conference Report

ABSTRACT

Quantitative Linguistics (QL) is an academic field that employs quantitative and statistical methods to explore language patterns and linguistic laws. From June 28th to 30th, 2023, the International Quantitative Linguistics Conference (QUALICO) 2023 took place in the picturesque and charming city of Lausanne, Switzerland. Co-organized by the International Quantitative Linguistics Association (IQLA) and the Department of Language and Information Sciences at the University of Lausanne, the conference is the first in-person QUALICO event after the COVID-19 pandemic. As the most prominent and authoritative international conference for QL, QUALICO 2023 demonstrates the current state and notable features of QL: 1) Maintain focus while keeping cutting-edge; 2) Encourage flourishing while celebrating diversity; 3) Exchange ideas while being open-minded. This gathering provides a platform for participants worldwide to present their research and engage in fruitful sharing, substantiating QL’s current state while shedding light on the prospects and emerging trends in the field.

Acknowledgments

The author would like to thank the committee of the International Quantitative Linguistics Association (IQLA) and the local committee at the University of Lausanne (UNIL) for their unwavering commitment and diligent efforts in organizing the event.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. Since its inception in 1994, IQLA has played a pivotal role in promoting ‘the use of mathematical and statistical methods in linguistic modelling, textual analysis, and related fields’. For more information on IQLA, see https://www.iqla.org/).

2. For more information on JQL, see https://www.tandfonline.com/journals/njql20.

3. For more information on QUALICO, see https://www.iqla.org/iqla_conferences.html. The other conferences that share some similarities with QUALICO, as suggested by one reviewer, include the Annual Meetings of the Association for Computational Linguistics (ACL) and the International Conference on the Statistical Analysis of Textual Data (JADT, Journées Internationales d’Analyse Statistique des Données Textuelles). ACL is the highest-level academic conference in the field of natural language processing and computational linguistics, covering dialogue, discourse, machine translation, phonology, semantics, and many more (For more information on ACL, see https://www.aclweb.org/portal/, and refer to Section 4 as well), and we also have the ACL Anthology which acts as the open source archive for computational linguistics and natural language processing’s scientific literature (Gildea et al., 2018). Meanwhile, JADT aims to provide a platform to showcase the latest advancements regarding theories, challenges, techniques, and implementations across various fields by taking statistical approaches to analyse lexical, textual, pragmatic, and discursive aspects of information conveyed through natural languages (Misuraca et al., 2022).

4. The first QUALICO meeting was held in Trier, Germany, and the subsequent conferences took place in Moscow in 1994, Helsinki in 1997, Prague in 2000, Athens (USA) in 2003, Trier in 2007 (a symposium organized by IQLA), Graz in 2009, Belgrade in 2012, Olomouc in 2014, Trier once more in 2016, Wrocław in 2018, Tokyo in 2021, and Lausanne in 2023.

5. For more information on QUALICO 2023, see https://wp.unil.ch/qualico2023/.

6. The author would like to thank Prof. Adam Pawłowski for providing precise and accurate information about the newly elected committee.

7. For generating Figures 1 and 2, certain preprocessing steps were undertaken. Specifically, the exclusion of stopwords (the stopword list utilized was sourced from the stop_words dataset in the tidytext package), numbers, and punctuation marks was carried out. Also, the lemmatize_strings() function in the textstem package was employed to lemmatize all words. In addition, in Figure 2, the proportion of each word was obtained by dividing its frequency by the total number of tokens of the entire corpus, and the equation for fitting rank and frequency to power law is y = 213.04*x^−0.62, R² = 0.97.