UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers

• URL: http://arxiv.org/abs/2309.16275v1
• Date: Thu, 28 Sep 2023 09:17:20 GMT
• Title: UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers
• Authors: Andrei Paraschiv and Mihai Dascalu
• Abstract summary: We address conspiracy theory detection as proposed by the ACTI @ EVALA 2023 shared task. Our methodology attained F1 scores of 85.71% in the binary classification and 91.23% for the fine-grained conspiracy topic classification, surpassing other competing systems.
• Score: 2.0046675283732887
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Conspiracy theories have become a prominent and concerning aspect of online discourse, posing challenges to information integrity and societal trust. As such, we address conspiracy theory detection as proposed by the ACTI @ EVALITA 2023 shared task. The combination of pre-trained sentence Transformer models and data augmentation techniques enabled us to secure first place in the final leaderboard of both sub-tasks. Our methodology attained F1 scores of 85.71% in the binary classification and 91.23% for the fine-grained conspiracy topic classification, surpassing other competing systems.

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