To maximize profits, social media depends on building echo chambers (filter bubbles) that silo users into like-minded digital communities and support more engagement, but limit their exposure to diverse views and encourage polarization.
Finnish and Danish researchers have developed an algorithm that boosts diversity of exposure on social networks, while still ensuring widely shared content.
The algorithm assigns numerical values to both social media content and users, representing a position on an ideological scale.
These numbers permit the calculation of a diversity exposure score for individual users, identifying those who would exchange content to maximize propagation of a wide spectrum of news and information viewpoints.
Antonis Matakos at Finland's Aalto University said the algorithm offers a feed for social media users that is at least three times more diverse than a simpler approach.
From IEEE Spectrum
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Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA
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