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Modeling news flows: How feedback loops influence citizens' beliefs and shape societies

Project description

Innovative model shedding light on news flows

Today, conspiracy theories and fake news including information from action groups or citizens are making their way to traditional media. This is thanks to feedback loops whereby the more something is shared, the more attention it may receive and the more people may share or act on the message, again increasing the number of shares. The EU-funded NEWSFLOWS project will use online field experiments, data donations and automated content analysis to study how information circulates in today’s media ecosystem. It aims to develop an alternative model on how information spreads that is based on feedback loops – an essential component for today’s complex system of information flows.


"Our beliefs about society are largely based on information that we encounter through media. This happens more and more in an ""unbundled” form: Single news items are distributed through sharing on social media, sorted by algorithms, and encountered on platforms on which they were not originally published. Many argue that this leads to so-called “echo chambers” and “filter bubbles”, communities of people that are only exposed to information they agree with. This is thought to lead to increasing polarization of society, and to a lack of diversity in people’s (virtual) communities.

But a growing body of evidence suggests that these metaphors are misleading.

In fact, as recent discussions on so-called “fake news” illustrate, biased and/or extreme information is not locked up in filter bubbles or echo chambers, but spreads from niche communities into mainstream media and politics. NEWSFLOWS develops an alternative model of how information spreads in today’s media ecosystem – a model based on so-called feedback loops, which are essential for the modern complex system of information flows. To give an example of a feedback loop: If a news item receives many shares on social media, this may let a recommendation algorithm show it to even more users (and journalists and politicans), making it more likely that they will act on it, again increasing the number of shares, etc. Crucially, neither the algorithm, nor the users, nor the writers alone determine the eventual spread, but a combination of their influences and feedback loops.

Theoretical models and empirical methods to study such feedback loops in the social sciences and humanities are scarce. NEWSFLOWS extends innovative methods as online field experiments, data donations, and automated content analysis to conduct such studies. This will greatly enhance the theoretical understanding of news flows, but also enable media organizations to develop products conforming to calls for ""responsible AI""."

Host institution

Net EU contribution
€ 647 261,00
1081 HV Amsterdam

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West-Nederland Noord-Holland Groot-Amsterdam
Activity type
Higher or Secondary Education Establishments
Total cost
€ 647 261,00

Beneficiaries (2)