Google Research @ Sydney Event
Honoured to have been selected to attend the Google Research @ Sydney Event at the first Google research facility in Australia with my colleague and lab mate.
About Me
Naomi Baes is a doctoral researcher at the intersection of Psychology and Natural Language Processing. Supported by an Australian Government Research Training Program Scholarship and supervised by Professor Nick Haslam and Dr Ekaterina Vylomova, her primary focus involves modelling conceptual change in mental health concepts using language models and historical corpora. With her supervisors, she co-developed SIBling, a multidimensional framework for evaluating semantic change across three major dimensions (Sentiment, Intensity, and Breadth) and led the development of LSC-Eval (with her supervisors and collaborators Dr Haim Dubossarsky and Raphaël Merx), a benchmarking framework that uses LLM-generated synthetic corpora to evaluate semantic change detection methods. Her work applies these frameworks to diverse corpora to model conceptual change and uncover its social and cultural drivers, and has been presented at leading venues including ACL 2024, ACL 2025 (upcoming), IC2S2 2025 (upcoming), and EMNLP (LChange’23). Naomi also contributes to SemEval tasks (BRIGHTER) and serves on program committees as a reviewer (NLP4Democracy; SEM2025).
Interests
- Computational Linguistics
- Computational Social Science
- Natural Language Processing
- Psychology
- Semantic Change
Education
PhD, Psychology/ Natural Language Processing
University of Melbourne (2023-)
Graduate Diploma in Psychology (Advanced) with Honours
University of Melbourne
Research Program
My research investigates how concepts change their meaning, focusing on mental health. With my PhD supervisors, I have developed a novel linguistic framework (SIBling) and measures to model lexical semantic change (LSC) along three dimensions that are typically overlooked by existing approaches.
Key Contributions:
- SIBling: A theoretical model integrating insights from historical linguistics and psychology, reducing six types of LSC into three core dimensions: Sentiment, Intensity, and Breadth (SIB). [Prototype]
- SIB Toolkit: Our computational implementation of SIBling, quantifying semantic change across SIB, plus related features (salience and thematic content). Designed for broad application across the social sciences and language domains (scientific, media, everyday).
- LSC-Eval: An evaluation framework that uses LLM-generated synthetic corpora to simulate kinds of LSC and validate LSC detection methods, identifying optimal dimension- and domain-specific approaches. [Prototype]
- Applications: I apply SIBling to trace the historical semantic evolution of mental health-related concepts (e.g., autism, schizophrenia), analysing related cultural dynamics like concept creep, pathologisation, and stigmatisation.
This program: (1) offers a multidimensional model of conceptual change (SIBling), (2) develops or identifies computational tools for its application, (3) establishes a principled evaluation framework for LSC detection methods (LSC-Eval), and (4) demonstrates its value through detailed case studies. This body of work lays the groundwork for future extensions across disciplines (e.g., law, humanities) and languages.
Featured Publications
Relevant Publications
(2025).
LSC-Eval: A General Framework to Evaluate Methods for Assessing Dimensions of Lexical Semantic Change Using LLM-Generated Synthetic Data.
ACL Findings (accepted).
(2024).
A Multidimensional Framework for Evaluating Lexical Semantic Change with Social Science Applications.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics.
(2024).
What should we call mental ill health? Historical shifts in the popularity of generic terms.
PLOS Mental Health.
(2024).
The structure and evolution of social psychology: a co-citation network analysis.
The Journal of Social Psychology.
(2024).
A search for commonalities in defining the common good: Using folk theories to unlock shared conceptions.
The British Journal of Social Psychology.
Invited Talks
Recent News
Quick Updates
July 22–24, 2025: Come meet me at IC2S2'25 (Norrköping, Sweden), the International Conference on Computational Social Science, where I’ll be presenting a poster on two frameworks for modeling — and evaluating methods for modeling — conceptual change: SIBling and LSC-Eval.
July 28, 2025: Come meet me at ACL 2025 The 63rd Annual Meeting of the Association for Computational Linguistics (Vienna, Austria) during Poster Session 5 (6:00–7:30 PM), where I’ll be presenting our ACL Findings paper — LSC-Eval: A General Evaluation Framework for Assessing Methods for Measuring Lexical Semantic Change with LLM-Generated Synthetic Data.
Excited to be interning with Change is Key! — an international research program developing computational tools to trace how language, society, and culture evolve. It applies NLP and corpus-based methods to detect semantic change and variation, supporting interdisciplinary research across linguistics, digital humanities, and the social sciences.
Serving on the SEM 2025 Program Committee — the 14th Joint Conference on Lexical and Computational Semantics (co-located with EMNLP in Suzhou, China).
Serving on the NLP4Democracy Program Committee — the first workshop on NLP for Democracy, held at COLM 2025 (Montreal, Canada).
New corpus data and scripts publicly available — see Resources tab.