# Mitigating Confirmation Bias on Twitter by Recommending Opposing Views

arXiv: https://arxiv.org/abs/1809.03901 · HTML: https://mlsanity.com/paper/1809.03901/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Sep 2018.

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

- [Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems](https://mlsanity.com/paper/2210.05662/) (2022)

## Abstract (arXiv)

In this work, we propose a content-based recommendation approach to increase exposure to opposing beliefs and opinions. Our aim is to help provide users with more diverse viewpoints on issues, which are discussed in partisan groups from different perspectives. Since due to the backfire effect, people's original beliefs tend to strengthen when challenged with counter evidence, we need to expose them to opposing viewpoints at the right time. The preliminary work presented here describes our first step into this direction. As illustrative showcase, we take the political debate on Twitter around the presidency of Donald Trump.