Reputation Systems in a polarised world need to take divisions into account. Often, divisive material gets more attention on social media.

The new systems we are developing aim to balance this, by recognising shared values and highlighting the importance of those contents that create bridges between otherwise distant communities. At the same time, our systems aim to improve the transparency and the accountability of the content producers, in particular for news, by keeping track of their histories. Our team is also leveraging cutting edge developments in Natural Language Processing to create an enriched sentiment analysis tool to identify discrete emotions and study their role in the information dynamics of media.