# Diversity in News Recommendations

arXiv: https://arxiv.org/abs/2005.09495 · HTML: https://mlsanity.com/paper/2005.09495/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2020.

## Built on by (most cited first, 3 of 3)

- [RADio -- Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations](https://mlsanity.com/paper/2209.13520/) (2022)
- [All Polarized but Still Different: a Multi-factorial Metric to Discriminate between Polarization Behaviors on Social Media](https://mlsanity.com/paper/2312.04603/) (2023)
- [Towards Multi-Aspect Diversification of News Recommendations Using Neuro-Symbolic AI for Individual and Societal Benefit](https://mlsanity.com/paper/2509.02220/) (2025)

## Abstract (arXiv)

News diversity in the media has for a long time been a foundational and uncontested basis for ensuring that the communicative needs of individuals and society at large are met. Today, people increasingly rely on online content and recommender systems to consume information challenging the traditional concept of news diversity. In addition, the very concept of diversity, which differs between disciplines, will need to be re-evaluated requiring a interdisciplinary investigation, which requires a new level of mutual cooperation between computer scientists, social scientists, and legal scholars. Based on the outcome of a multidisciplinary workshop, we have the following recommendations, directed at researchers, funders, legislators, regulators, and the media industry: 1. Do more research on news recommenders and diversity. 2. Create a safe harbor for academic research with industry data. 3. Optimize the role of public values in news recommenders. 4. Create a meaningful governance framework. 5. Fund a joint lab to spearhead the needed interdisciplinary research, boost practical innovation, develop. reference solutions, and transfer insights into practice.