# UPB @ ACTI: Detecting Conspiracies using fine tuned Sentence Transformers

arXiv: https://arxiv.org/abs/2309.16275 · HTML: https://mlsanity.com/paper/2309.16275/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 31 references that are in the map.
- First posted on arXiv 28 Sep 2023.

## Builds on (most cited first, 12 of 12)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Efficient Few-Shot Learning Without Prompts](https://mlsanity.com/paper/2209.11055/) (2022)
- [Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation](https://mlsanity.com/paper/2004.14983/) (2020)
- [Do Platform Migrations Compromise Content Moderation? Evidence from r/The_Donald and r/Incels](https://mlsanity.com/paper/2010.10397/) (2020)
- [Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banning](https://mlsanity.com/paper/2209.09803/) (2022)
- [Catching Zika Fever: Application of Crowdsourcing and Machine Learning for Tracking Health Misinformation on Twitter](https://mlsanity.com/paper/1707.03778/) (2017)
- [A Golden Age: Conspiracy Theories' Relationship with Misinformation Outlets, News Media, and the Wider Internet](https://mlsanity.com/paper/2301.10880/) (2023)
- [Understanding Online Migration Decisions Following the Banning of Radical Communities](https://mlsanity.com/paper/2212.04765/) (2022)
- [Disentangling Active and Passive Cosponsorship in the U.S. Congress](https://mlsanity.com/paper/2205.09674/) (2022)
- [Detecting Conspiracy Theory Against COVID-19 Vaccines](https://mlsanity.com/paper/2211.13003/) (2022)
- [Empowering Sentence Encoders with Prompting and Label Retrieval for Zero-shot Text Classification](https://mlsanity.com/paper/2212.10391/) (2022)
- [Climate Change Conspiracy Theories on Social Media](https://mlsanity.com/paper/2107.03318/) (2021)

## Abstract (arXiv)

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.