# Tracking Discourse Influence in Darknet Forums

arXiv: https://arxiv.org/abs/2202.02081 · HTML: https://mlsanity.com/paper/2202.02081/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 15 references that are in the map.
- First posted on arXiv 4 Feb 2022.

## Builds on (most cited first, 6 of 6)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [Universal Sentence Encoder](https://mlsanity.com/paper/1803.11175/) (2018)
- [Bringing UMAP Closer to the Speed of Light with GPU Acceleration](https://mlsanity.com/paper/2008.00325/) (2020)
- [Individuals, Institutions, and Innovation in the Debates of the French Revolution](https://mlsanity.com/paper/1710.06867/) (2017)
- [De-Anonymizing Text by Fingerprinting Language Generation](https://mlsanity.com/paper/2006.09615/) (2020)

## Abstract (arXiv)

This technical report documents our efforts in addressing the tasks set forth by the 2021 AMoC (Advanced Modelling of Cyber Criminal Careers) Hackathon. Our main contribution is a joint visualisation of semantic and temporal features, generating insight into the supplied data on darknet cybercrime through the aspects of novelty, transience, and resonance, which describe the potential impact a message might have on the overall discourse in darknet communities. All code and data produced by us as part of this hackathon is publicly available.