Simon Hengchen

Simon Hengchen is a former staff member, who quit on 2022-12-31.

PhD in Information Science
MSc in Information Science
MA in Germanic Languages

My research focus is lexical semantic change: when, why, and how words change meaning.

I work within the Towards Automatic Detection of Language Change project (2019 - 2022) with Nina Tahmasebi, Richard Johansson and Maria Koptjevskaja Tamm.

Recently, we have run the SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection with colleagues.

Projects - current

Change is Key!

This program has two main aims, firstly to develop corpus-based methods for detecting semantic change (over time) and variation (across social groups and media). This will create general tools for the study and detection of language change at large-scale and directly benefit historical linguistics and lexicography. Secondly, we will collaborate with researchers from social sciences, gender studies, and literature to answer their research questions. We will develop tools, evaluation data, and research methodology for their specific needs.

Projects - finished

Towards Computational Lexical Semantic Change Detection

In this project, we aim to find automatic, corpus-based methods for detecting semantic change and lexical replacement for Swedish and English.

Publications

2023

Aleksandrs Berdicevskis, Gerlof Bouma, Robin Kurtz, Felix Morger, Joey Öhman, Yvonne Adesam, Lars Borin, Dana Dannélls, Markus Forsberg, Tim Isbister, Anna Lindahl, Martin Malmsten, Faton Rekathati, Magnus Sahlgren, Elena Volodina, Love Börjeson, Simon Hengchen, Nina Tahmasebi (2023): Superlim: A Swedish Language Understanding Evaluation Benchmark, in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, December 6-10, 2023, Singapore / Houda Bouamor, Juan Pino, Kalika Bali (Editors)
Nina Tahmasebi, Syrielle Montariol, Haim Dubossarsky, Andrey Kutuzov, Simon Hengchen, David Alfter, Francesco Periti, Pierluigi Cassotti (2023): Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change, LChange'23, December 6th, 2023, Singapore

2022

Nina Tahmasebi, Syrielle Montariol, Andrey Kutuzov, Simon Hengchen, Haim Dubossarsky, Lars Borin (2022): Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, May 26-27, 2022, Dublin, Ireland

2021

Simon Hengchen, Kate Viloria, Andrey Indukaev (2021): SBX-HY at RuShiftEval 2021: Доверяй, но проверяй, in Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference “Dialogue 2021,” Moscow, June 16–19, 2021
Simon Hengchen, Ruben Ros, Jani Marjanen, Mikko Tolonen (2021): A data-driven approach to studying changing vocabularies in historical newspaper collections, in Digital Scholarship in the Humanities, volume 36, issue Supplement 2, pages 109–126
Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg, Haim Dubossarsky (2021): Challenges for computational lexical semantic change, in Computational approaches to semantic change / Tahmasebi, Nina, Borin, Lars, Jatowt, Adam, Yang, Xu, Hengchen, Simon (eds.), pages 341-372
Matteo Romanello, Simon Hengchen (2021): Detecting Text Reuse with Passim, in The Programming Historian, volume 10
Valerio Perrone, Simon Hengchen, Marco Palma, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray (2021): Lexical semantic change for Ancient Greek and Latin, in Computational approaches to semantic change, pages 287-310
Nina Tahmasebi, Lars Borin, Adam Jatowt, Yang Xu, Simon Hengchen (2021): Computational approaches to semantic change
Jani Marjanen, Elaine Zosa, Simon Hengchen, Lidia Pivovarova, Mikko Tolonen (2021): Topic Modelling Discourse Dynamics in Historical Newspapers, in CEUR Workshop Proceedings. Post-Proceedings of the 5th Conference Digital Humanities in the Nordic Countries (DHN 2020), Riga, Latvia, October 21-23, 2020
Quan Duong, Mika Hämäläinen, Simon Hengchen (2021): An Unsupervised method for OCR Post-Correction and Spelling Normalisation for Finnish, in Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), May 31–2 June, 2021, Reykjavik, Iceland (online)
Simon Hengchen, Nina Tahmasebi (2021): SuperSim: a test set for word similarity and relatedness in Swedish, in Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), May 31-June 2 2021, Reykjavik, Iceland (online)
Simon Hengchen, Nina Tahmasebi (2021): A Collection of Swedish Diachronic Word Embedding Models Trained on Historical Newspaper Data, in Journal of Open Humanities Data, volume 7, issue 2, pages 1-7

2020

Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky, Nina Tahmasebi (2020): SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection, in Proceedings of the Fourteenth Workshop on Semantic Evaluation (SemEval2020), Barcelona, Spain (Online), December 12, 2020.
Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky, Nina Tahmasebi (2020): Post-Evaluation Data for SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection, in Zenodo
Nina Tahmasebi, Simon Hengchen, Dominik Schlechtweg, Barbara McGillivray, Haim Dubossarsky (2020): Swedish Test Data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection, in Zenodo
Esteban Frossard, Mickael Coustaty, Antoine Doucet, Adam Jatowt, Simon Hengchen (2020): Dataset for Temporal Analysis of English-French Cognates, in Proceedings of The 12th Language Resources and Evaluation Conference
Barbara McGillivray, Beatrice Alex, Sarah Ames, Guyda Armstrong, David Beavan, Arianna Ciula, Giovanni Colavizza, James Cummings, David De Roure, Adam Farquhar, Simon Hengchen, Anouk Lang, James Loxley, Eirini Goudarouli, Federico Nanni, Andrea Nini, Julianne Nyhan, Nicola Osborne, Thierry Poibeau, Mia Ridge, Sonia Ranade, James Smithies, Melissa Terras, Andreas Vlachidis, Pip Willcox (2020): The challenges and prospects of the intersection of humanities and data science: A White Paper from The Alan Turing Institute, in White paper

2019

Haim Dubossarsky, Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg (2019): Time for change: Evaluating models of semantic change without evaluation tasks, in Cambridge Language Sciences Annual Symposium 2019 : Perspectives on Language Change
Haim Dubossarsky, Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg (2019): Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change, in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, July 28 - August 2, 2019 / Anna Korhonen, David Traum, Lluís Màrquez (Editors)
Nina Tahmasebi, Simon Hengchen (2019): The Strengths and Pitfalls of Large-Scale Text Mining for Literary Studies, in Samlaren : tidskrift för svensk litteraturvetenskaplig forskning, volume 140, pages 198–227
Mika Hämäläinen, Simon Hengchen (2019): From the paft to the fiiture: A fully automatic NMT and word embeddings method for OCR post-correction, in International Conference Recent Advances in Natural Language Processing, RANLP, Varna, Bulgaria, 2–4 September, 2019
Valerio Perrone, Marco Palma, Simon Hengchen, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray (2019): GASC: Genre-Aware Semantic Change for Ancient Greek, in Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change
Mark J. Hill, Simon Hengchen (2019): Quantifying the impact of dirty OCR on historical text analysis: Eighteenth Century Collections Online as a case study, in Digital Scholarship in the Humanities, volume 34, issue 4, pages 825-843

2017

Simon Hengchen (2017): When Does it Mean? Detecting Semantic Change in Historical Texts

Role

Guest researcher (Gästforskare)

Email

simon.hengchen@gu.se

Blog entries and news

2020-12-03 News: New diachronic word embeddings models trained on newspaper data

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