MN
M.A. Narkar
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1
Student report
(2025)
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C. Hernando De La Fuente, K.J. Trouwee, M.P. Jimenez Moreno, S.X. Li, M.A. Narkar, B.V. van Vliet, Amir Niknam, B.J.E. de Bruin
The spread of climate change mis- and disinformation poses a big threat to society; addressing this is the goal of the Joint Interdisciplinary Project (JIP) 6.1.1, in collaboration with the National Police. This report details the development of the Climate Disinformation Tracker, an open-source proof-ofconcept tool designed to trace the earliest online occurrence of climate denial narratives on Platform X and provide insightful visualizations of related tweets. The methodology, adapted from the DisTrack architecture, utilizes KeyBERT for keyword extraction and a custom scraping pipeline relying on the Nitter front-end for data retrieval, followed by mDeBERTa-v3-base-mnli-xnli for natural language inference (NLI) to classify posts as entailing, neutral, or contradictory to a user-provided claim. Validation testing demonstrated that the tool correctly identified the source tweet in 72% of claims when incorporating the synonym component, thus validating the potential of this approach for misinformation
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context. ...
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context. ...
The spread of climate change mis- and disinformation poses a big threat to society; addressing this is the goal of the Joint Interdisciplinary Project (JIP) 6.1.1, in collaboration with the National Police. This report details the development of the Climate Disinformation Tracker, an open-source proof-ofconcept tool designed to trace the earliest online occurrence of climate denial narratives on Platform X and provide insightful visualizations of related tweets. The methodology, adapted from the DisTrack architecture, utilizes KeyBERT for keyword extraction and a custom scraping pipeline relying on the Nitter front-end for data retrieval, followed by mDeBERTa-v3-base-mnli-xnli for natural language inference (NLI) to classify posts as entailing, neutral, or contradictory to a user-provided claim. Validation testing demonstrated that the tool correctly identified the source tweet in 72% of claims when incorporating the synonym component, thus validating the potential of this approach for misinformation
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context.
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context.