# Digital Persuasion: Understanding the Impact of Online Influencers on Public Opinion

arXiv: https://arxiv.org/abs/2609.16062 · HTML: https://mlsanity.com/paper/2609.16062/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 18 references that are in the map.
- First posted on arXiv 13 Sep 2026.

## Builds on (most cited first, 9 of 9)

- [Opinion Maximization in Social Networks](https://mlsanity.com/paper/1301.7455/) (2013)
- [Predicting Opinion Dynamics via Sociologically-Informed Neural Networks](https://mlsanity.com/paper/2207.03990/) (2022)
- [Opinion Optimization in Directed Social Networks](https://mlsanity.com/paper/2306.16847/) (2023)
- [Opinion dynamics in social networks with stubborn agents: an issue-based perspective](https://mlsanity.com/paper/1609.03465/) (2016)
- [Local Edge Dynamics and Opinion Polarization](https://mlsanity.com/paper/2111.14020/) (2021)
- [Dynamics of opinion polarization](https://mlsanity.com/paper/2206.06134/) (2022)
- [Modeling communication asymmetry and content personalization in online social networks](https://mlsanity.com/paper/2301.01478/) (2023)
- [Echo chamber formation sharpened by priority users](https://mlsanity.com/paper/2312.09358/) (2023)
- [Friedkin-Johnsen Model for Opinion Dynamics on Signed Graphs](https://mlsanity.com/paper/2407.10680/) (2024)

## Built on by (most cited first, 1 of 1)

- [Digital Twins for Opinion Dynamics: A Generative LLM Framework for Social Networks](https://mlsanity.com/paper/2609.19913/) (2026)

## Abstract (arXiv)

The studying of opinion dynamics and its propagation within social networks is crucial for addressing a wide range of challenges, including political polarization, public health, and marketing strategies. In this work, we study the problem of opinion dynamics by proposing a framework based on Friedkin-Johnsen (FJ) to identifies influential users and study their impact on dynamics opinions of community. The FJ model assume each individual have two opinions: initial and expressed. Through a series of initial opinion manipulation experiments, the proposed framework assesses the impact of influential versus random users on the overall community opinion. The proposed framework is validated using a tweet dataset representing the U.S. presidential election. The results shows that influencers with highest influencing score, significantly shift the overall community opinion. Moreover, the results shows that the impact of influencers not limited to direct neighbors , but beyond it, to their neighbors of neighbors . This study demonstrates how digital influencers on social media can shape public opinion regarding a subject or cause.