UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence
  Transformers
Andrei Paraschiv Mihai Dascalu
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.