LChange'23 is the fourth workshop for computational approaches to historical language change with the focus on digital text corpora. Come join us for this exciting adventure!
The workshop builds upon its first iteration in 2019, and the subsequent events (2021, 2022). It will be colocated with EMNLP 2023 in Singapore, as a hybrid event. The workshop dates are not yet fixed.
We hope to make this fourth edition another resounding success!
The call for papers will be similar to last time: all aspects around computational approaches to historical language change with the focus on digital text corpora. If you have published in the field previously, and are inrerested in helping out in the PC to review papers, send us an email. LChange'19 resulted in a book on Computational approaches to semantic change, and this year, we are considering a special issue journal for invited workshop papers.
- September 1, 2023: Paper submission
- October 6, 2023: Notification of acceptance
- October 18, 2023: Camera-ready papers due
- December 6-7, 2023: Workshop date
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
To be announced. If you have any good suggestions, or anyone you would like to listen to, please contact us.
We accept two types of submissions, long and short papers, following the EMNLP 2023 style (you can also directly use the Overleaf template), and the ACL submission policy. Model and dataset papers fall into the short paper category.
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’23 also welcomes papers focusing on releasing a dataset or a model; these papers fall into the short paper category.
if you have any questions.
Francesco Periti , and
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 Priscilla Rasmussen, in case of any issues.
- 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.
- 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.