Computational approaches to semantic change

Nina Tahmasebi   Lars Borin   Adam Jatowt   Yang Xu   Simon Hengchen  


Semantic change — how the meanings of words change over time — has preoccupied scholars since well before modern linguistics emerged in the late 19th and early 20th century, ushering in a new methodological turn in the study of language change. Compared to changes in sound and grammar, semantic change is the least  understood. Ever since, the study of semantic change has progressed steadily, accumulating a vast store of knowledge for over a century, encompassing many languages and language families.

Historical linguists also early on realized the potential of computers as research tools, with papers at the very first international conferences in computational linguistics in the 1960s. Such computational studies still tended to be small-scale, method-oriented, and qualitative. However, recent years have witnessed a sea-change in this regard. Big-data empirical quantitative investigations are now coming to the forefront, enabled by enormous advances in storage capability and processing power. Diachronic corpora have grown beyond imagination, defying exploration by traditional manual qualitative methods, and language technology has become increasingly data-driven and semantics-oriented. These developments present a golden opportunity for the empirical study of semantic change over both long and short time spans.

A major challenge presently is to integrate the hard-earned  knowledge and expertise of traditional historical linguistics with  cutting-edge methodology explored primarily in computational linguistics.

The idea for the present volume came out of a concrete response to this challenge.  The 1st International Workshop on Computational Approaches to Historical Language Change (LChange'19), at ACL 2019, brought together scholars from both fields.

This volume offers a survey of this exciting new direction in the study of semantic change, a discussion of the many remaining challenges that we face in pursuing it, and considerably updated and extended versions of a selection of the contributions to the LChange'19 workshop, addressing both more theoretical problems —  e.g., discovery of "laws of semantic change" — and practical applications, such as information retrieval in longitudinal text archives.


  • Survey of computational approaches to lexical semantic change detection
    Nina Tahmasebi, Lars Borin, Adam Jatowt
  • Semantic changes in harm-related concepts in English
    Ekaterina Vylomova, Nick Haslam
  • Computation of semantic change in scientific concepts: Case study of the "circular economy"
    Sampriti Mahanty, Frank Boons, Julia Handl, Riza Batista-Navarro
  • Semantic change in Swedish – from a lexicographic perspective
    Stellan Petersson, Emma Sköldberg
  • Historical changes in semantic weights of sub-word units
    Yang Xu, Zheng-sheng Zhang
  • Chaining algorithms and historical adjective extension
    Karan Grewal, Yang Xu
  • Cross-lingual laws of semantic change
    Ana-Sabina Uban, Alina Maria Ciobanu, Liviu P. Dinu
  • Structured representation of temporal document collections by diachronic linguistic periodization
    Yijun Duan, Adam Jatowt, Masatoshi Yoshikawa
  • Lexical semantic change for Ancient Greek and Latin
    Valerio Perrone, Simon Hengchen, Marco Palma, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray
  • Computational approaches to lexical semantic change
    Visualization systems and novel applications
    Adam Jatowt, Nina Tahmasebi, Lars Borin
  • Challenges for computational lexical semantic change
    Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg, Haim Dubossarsky



Nina Tahmasebi, Språkbanken Text, University of Gothenburg

Nina Tahmasebi is an associate professor in NLP at Språkbanken Text, University of Gothenburg. She holds a PhD in computer science from the University of Hanover and L3S Research Center, and a Masters in Applied Mathematics from Chalmers University of Technology.
She has been conducting research on all aspects of computational lexical semantic change since 2008 – from developing theory, methods, evaluation techniques, to creating resources. In addition, Nina also studies related problems in NLP, such as disseminating computational models of language for text mining and Digital Humanities. She takes a particular interest in ensuring that answers found from large-scale text are an accurate representation of the underlying information stored in the text. 

Lars Borin, University of Gothenburg

Lars Borin is professor of natural language processing at the University of Gothenburg, with a background in comparative Slavic and Finno-Ugric linguistics and in computation. His research interests include studying computational lexical semantics from a cross-linguistic perspective, developing and applying computational linguistic methods to problems of historical-comparative, typological and areal linguistics, and language-centered digital humanities.

Adam Jatowt, University of Innsbruck

Adam Jatowt is a Professor at the Computer Science department of the University of Innsbruck. He is also affiliated with the Digital Science Center at the University of Innsbruck. He received his Ph.D. from the University of Tokyo, Japan in 2005 and has worked as an Assistant and Associate Professor at Kyoto University. His research interests include broad topics in natural language processing, information retrieval, digital humanities and digital libraries. Adam has published over 150 research papers in international conferences and journals. He is on the editorial board of IP&M, JASIST, IJDL, JIIS and IEEE JSC journals.

Yang Xu, University of Toronto

Yang Xu is Assistant Professor in the Department of Computer Science and the Cognitive Science Program at the University of Toronto. He obtained his BA/MEng from the University of Cambridge and a PhD in Machine Learning from Carnegie Mellon University. He took a postdoctoral position in the epartment of Linguistics at University of California, Berkeley. His current research intersects language, computation, and cognition, with an emphasis on understanding the time-varying nature of the human lexicon.

Simon Hengchen, Göteborgs Universitet

Simon Hengchen (1988) holds master’s degrees in Germanic languages and in Information Science from the Université libre de Bruxelles (Belgium), where he also obtained a PhD in Information Science. His research focusses on computational approaches to lexical semantic change. After a postdoc in a computational history group in Helsinki, Simon is currently employed at Göteborgs Universitet (Sweden) as a researcher and at the Université de Genève (Switzerland) as a lecturer.

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February 26, 2021
LaTeX source on GitHub
Cite as
Tahmasebi, Nina, Borin, Lars, Jatowt, Adam, Xu, Yang & Hengchen, Simon (eds.). 2021. Computational approaches to semantic change. (Language Variation 6). Berlin: Language Science Press. DOI: 10.5281/zenodo.5040241


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