The workshop builds upon its first iteration in 2019, and the subsequent events (2021, 2022, 2023). It will be colocated with ACL 2024 in Bangkok (Thailand), as a hybrid event. The workshop will take place on Thursday 15 August 2024.

We hope to make this fifth edition another resounding success!

The main topic of the workshop remains the same: all aspects around computational approaches to historical language change with the focus on digital text corpora. LChange'19 resulted in a book on Computational approaches to semantic change.

Important Dates

• May 10, 2024: Paper submission
• June 20, 2024: Notification of acceptance
• June 30, 2024: Camera-ready papers due
• August 15, 2024: Workshop date

Workshop Topics

This workshop explores state-of-the-art computational methodologies, theories and digital text resources on exploring the time-varying nature of human language.

The aim of this workshop is three-fold. First, we want to provide pioneering researchers who work on computational methods, evaluation, and large-scale modelling of language change an outlet for disseminating cutting-edge research on topics concerning language change. We want to utilize this workshop as a platform for sharing state-of-the-art research progress in this fundamental domain of natural language research.

Second, in doing so we want to bring together domain experts across disciplines by connecting researchers in historical linguistics with those that develop and test computational methods for detecting semantic change and laws of semantic change; and those that need knowledge (of the occurrence and shape) of language change, for example, in digital humanities and computational social sciences where text mining is applied to diachronic corpora subject to e.g., lexical semantic change.

Third, the detection and modelling of language change using diachronic text and text mining raise fundamental theoretical and methodological challenges for future research.

Besides these goals, this workshop will also support discussion on the evaluation of computational methodologies for uncovering language change. SemEval2020 Task1 on unsupervised detection of lexical semantic change attracted three figure submission numbers and a total of 21 submitted system papers. Since then, three more tasks have been completed in Italian, Russian, and Spanish.

We invite original research papers from a wide range of topics, including but not limited to:

• Novel methods for detecting diachronic semantic change and lexical replacement
• Automatic discovery and quantitative evaluation of laws of language change
• Computational theories and generative models of language change
• Sense-aware (semantic) change analysis
• Diachronic word sense disambiguation
• Novel methods for diachronic analysis of low-resource languages
• Novel methods for diachronic linguistic data visualization
• Novel applications and implications of language change detection
• Quantification of sociocultural influences on language change
• Cross-linguistic, phylogenetic, and developmental approaches to language change
• Novel datasets for cross-linguistic and diachronic analyses of language

Submissions

URL for submissions: https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/LChange.

We accept two types of submissions, long and short papers, following the ACL 2024 style (see eg the Overleaf template), and the ACL submission policy.

Long and short papers may consist of up to eight (8) and four (4) pages of content, respectively, plus unlimited references; final versions will be given one additional page of content so that reviewers' comments can be taken into account.

LChange’24 also welcomes papers focusing on releasing a dataset or a model; these papers fall into the short paper category. To encourage model and dataset sharing at the reviewing phase, model and dataset papers do not need to be anonymous.

Accepted papers will be presented orally or as posters and included in the workshop proceedings. Submissions are open to all, and are to be submitted anonymously. All papers will be refereed through a double-blind peer review process by at least three reviewers with final acceptance decisions made by the workshop organizers.

Shared Task

This year, and echoing LChange 22 in Dublin, we are happy to host a shared task within LChange: the AXOLOTL-24 Shared Task on Explainable Semantic Change Modeling. AXOLOTL-24 stands for “Ascertain and eXplain Overhauls of the Lexicon Over Time at LChange'24” and is organised by Mariia Fedorova and Andrey Kutuzov (University of Oslo), Timothee Mickus, Niko Partanen and Janine Siewert (University of Helsinki), and Elena Spaziani (Sapienza University Rome).

The shared task presents two subtasks:

• Finding the target word usages associated with new, gained senses
• Describing these senses in a way that facilitates understanding and lexicographical research.

More information, including timeline and instructions, is available on https://github.com/ltgoslo/axolotl24_shared_task/.

Contact

Contact us if you have any questions.

If you have published in the field previously, and are inrerested in helping out in the PC to review papers, send us an email.

Organisers: Nina Tahmasebi, Syrielle Montariol, Andrey Kutuzov Simon Hengchen, David Alfter, Francesco Periti , and Pierluigi Cassotti.

Anti-Harassment Policy

Our workshop highly values the open exchange of ideas, the freedom of thought and expression, and respectful scientific debate. We support and uphold the ACL Anti-Harassment policy, and any workshop participant should feel free to contact any of the workshop organisers or ACL (acl@aclweb.org), in case of any issues.

References:

• Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg, Haim Dubossarsky. Challenges for Computational Lexical Semantic Change. Nina Tahmasebi, Lars Borin, Adam Jatowt, Yang Xu, Simon Hengchen (eds). Computational Approaches to Semantic Change. Berlin: Language Science Press.
• Nina Tahmasebi, Adam Jatowt, Lars Borin. Survey of Computational Approaches to Lexical Semantic Change Detection. Nina Tahmasebi, Lars Borin, Adam Jatowt, Yang Xu, Simon Hengchen (eds). Computational Approaches to Semantic Change. Berlin: Language Science Press.
• Andrey Kutuzov, Lilja Øvrelid, Terrence Szymanski, and Erik Velldal. 2018. Diachronic word embeddings and semantic shifts: a survey. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1384–1397, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
• Francesco Periti and Nina TahmasebiA Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Change. (2024) arXiv:2402.12011.
• Stefano Montanelli and Francesco Periti, A Survey on Contextualised Semantic Shift Detection. (2023) arXiv:2304.01666.
• Pierluigi Cassotti, Lucia Siciliani, Marco DeGemmis, Giovanni Semeraro, Pierpaolo Basile, XL-LEXEME: WiC Pretrained Model for Cross-Lingual LEXical sEMantic changE. (2023) In Proc. of ACL2023
• Francesco Periti, Sergio Picascia, Stefano Montanelli, Alfio Ferrara, and Nina Tahmasebi, Studying Word Meaning Evolution through Incremental Semantic Shift Detection: A Case Study of Italian Parliamentary Speeches. (2023) TechRxiv.
• Baayen, R. Harald. 2001. Word Frequency Distributions. Dordrecht: Kluwer Academic Publishers.
• Koplenig, Alexander. 2015. The Impact of Lacking Metadata for the Measurement of Cultural and Linguistic Change Using the Google Ngram Data Sets—Reconstructing the Composition of the German Corpus in Times of WWII. Digital Scholarship in the Humanities fqv037. https://doi.org/10.1093/llc/fqv037.
• Koplenig, Alexander, Sascha Wolfer & Carolin Müller-Spitzer. 2019. Studying Lexical Dynamics and Language Change via Generalized Entropies: The Problem of Sample Size. Entropy 21(5). https://doi.org/10.3390/e21050464. http://www.mdpi.com/1099-4300/21/5/464.
• Labov, William. 1994. Principles of linguistic change (Language in Society 20). Oxford, UK ; Cambridge [Mass.]: Blackwell.
• Michel, Jean-Baptiste, Yuan Kui Shen, Aviva Presser Aiden, Adrian Verses, Matthew K. Gray, The Google Books Team, Joseph P. Pickett, et al. 2010. Quantitative Analysis of Culture Using Millions of Digitized Books (Supporting Online Material II). Science 331(14). http://www.sciencemag.org/content/331/6014/176/suppl/DC1 (5 March, 2014).
• Pechenick, Eitan Adam, Christopher M. Danforth & Peter Sheridan Dodds. 2015. Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution. (Ed.) Alain Barrat. PLOS ONE 10(10). e0137041. https://doi.org/10.1371/journal.pone.0137041.
• Szmrecsanyi, Benedikt. 2016. About text frequencies in historical linguistics: Disentangling environmental and grammatical change. Corpus Linguistics and Linguistic Theory 12(1). 153–171. https://doi.org/10.1515/cllt-2015-0068.