# Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources

arXiv: https://arxiv.org/abs/1805.12032 · HTML: https://mlsanity.com/paper/1805.12032/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2018.

## Built on by (most cited first, 4 of 4)

- [It's about Time: Rethinking Evaluation on Rumor Detection Benchmarks using Chronological Splits](https://mlsanity.com/paper/2302.03147/) (2023)
- [Identifying and Characterizing Active Citizens who Refute Misinformation in Social Media](https://mlsanity.com/paper/2204.10080/) (2022)
- [News Source Credibility Assessment: A Reddit Case Study](https://mlsanity.com/paper/2402.10938/) (2024)
- [Proactive Defense: Compound AI for Detecting Persuasion Attacks and Measuring Inoculation Effectiveness](https://mlsanity.com/paper/2511.21749/) (2025)

## Abstract (arXiv)

In the age of social news, it is important to understand the types of reactions that are evoked from news sources with various levels of credibility. In the present work we seek to better understand how users react to trusted and deceptive news sources across two popular, and very different, social media platforms. To that end, (1) we develop a model to classify user reactions into one of nine types, such as answer, elaboration, and question, etc, and (2) we measure the speed and the type of reaction for trusted and deceptive news sources for 10.8M Twitter posts and 6.2M Reddit comments. We show that there are significant differences in the speed and the type of reactions between trusted and deceptive news sources on Twitter, but far smaller differences on Reddit.