UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers
September 28, 2023 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Andrei Paraschiv, Mihai Dascalu
arXiv ID
2309.16275
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
0
Venue
arXiv.org
Last Checked
6 months ago
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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