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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.08777 |
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| _version_ | 1866908314733903872 |
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| author | Susnjak, Teo Palffy, Cole Zimina, Tatiana Altynbekova, Nazgul Garg, Kunal Gilbert, Leona |
| author_facet | Susnjak, Teo Palffy, Cole Zimina, Tatiana Altynbekova, Nazgul Garg, Kunal Gilbert, Leona |
| contents | The scientific discourse surrounding Chronic Lyme Disease (CLD) and Post-Treatment Lyme Disease Syndrome (PTLDS) has evolved over the past twenty-five years into a complex and polarised debate, shaped by shifting research priorities, institutional influences, and competing explanatory models. This study presents the first large-scale, systematic examination of this discourse using an innovative hybrid AI-driven methodology, combining large language models with structured human validation to analyse thousands of scholarly abstracts spanning 25 years. By integrating Large Language Models (LLMs) with expert oversight, we developed a quantitative framework for tracking epistemic shifts in contested medical fields, with applications to other content analysis domains. Our analysis revealed a progressive transition from infection-based models of Lyme disease to immune-mediated explanations for persistent symptoms. This study offers new empirical insights into the structural and epistemic forces shaping Lyme disease research, providing a scalable and replicable methodology for analysing discourse, while underscoring the value of AI-assisted methodologies in social science and medical research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_08777 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and Divides Susnjak, Teo Palffy, Cole Zimina, Tatiana Altynbekova, Nazgul Garg, Kunal Gilbert, Leona Computers and Society Computation and Language The scientific discourse surrounding Chronic Lyme Disease (CLD) and Post-Treatment Lyme Disease Syndrome (PTLDS) has evolved over the past twenty-five years into a complex and polarised debate, shaped by shifting research priorities, institutional influences, and competing explanatory models. This study presents the first large-scale, systematic examination of this discourse using an innovative hybrid AI-driven methodology, combining large language models with structured human validation to analyse thousands of scholarly abstracts spanning 25 years. By integrating Large Language Models (LLMs) with expert oversight, we developed a quantitative framework for tracking epistemic shifts in contested medical fields, with applications to other content analysis domains. Our analysis revealed a progressive transition from infection-based models of Lyme disease to immune-mediated explanations for persistent symptoms. This study offers new empirical insights into the structural and epistemic forces shaping Lyme disease research, providing a scalable and replicable methodology for analysing discourse, while underscoring the value of AI-assisted methodologies in social science and medical research. |
| title | The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and Divides |
| topic | Computers and Society Computation and Language |
| url | https://arxiv.org/abs/2504.08777 |