# The Anatomy Spread of Online Opinion Polarization: The Pivotal Role of Super-Spreaders in Social Networks

arXiv: https://arxiv.org/abs/2401.01349 · HTML: https://mlsanity.com/paper/2401.01349/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 57 references that are in the map.
- First posted on arXiv 27 Nov 2023.

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

- [Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery](https://mlsanity.com/paper/1703.05921/) (2017)
- [Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning](https://mlsanity.com/paper/1712.03141/) (2017)
- [Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection](https://mlsanity.com/paper/1802.09089/) (2018)
- [Political Discourse on Social Media: Echo Chambers, Gatekeepers, and the Price of Bipartisanship](https://mlsanity.com/paper/1801.01665/) (2018)
- [Opinion dynamics: models, extensions and external effects](https://mlsanity.com/paper/1605.06326/) (2016)
- [Opinion Dynamics Theory for Analysis of Consensus Formation and Division of Opinion on the Internet](https://mlsanity.com/paper/1812.11845/) (2018)

## Abstract (arXiv)

The study investigates the role of 'superspreaders' in shaping opinions within networks, distinguishing three types: A, B, and C. Type A has a significant influence in shaping opinions, Type B acts as a counterbalance to A, and Type C functions like media, providing an objective viewpoint and potentially regulating A and B's influence. The research uses a confidence coefficient and z-score to survey superspreaders' behaviors, with a focus on the conditions affecting group dynamics and opinion formation, including environmental factors and forgetfulness over time. The findings offer insights for improving online communication security and understanding social influence. This paper is partially an attempt to utilize "Generative AI" and was written with educational intent. There are currently no plans for it to become a peer-reviewed paper.