In current behavioral debate, fake news is often treated as a static entity—finite in nature, potentially subject to fact-checking, and lacking evolutionary characteristics. We aim to bridge existing domains of behavioral research on fake news by introducing an evolutionary model based on three fundamental mechanisms: variation (what users generate), selection (what users pay attention to), and retention (what users share). This model accounts for the dynamic transformation of non-fake content into fake news, and vice versa.
Becoming fake: an evolutionary model of fake news
Jacopo Marchetti
Writing – Original Draft Preparation
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2025-01-01
Abstract
In current behavioral debate, fake news is often treated as a static entity—finite in nature, potentially subject to fact-checking, and lacking evolutionary characteristics. We aim to bridge existing domains of behavioral research on fake news by introducing an evolutionary model based on three fundamental mechanisms: variation (what users generate), selection (what users pay attention to), and retention (what users share). This model accounts for the dynamic transformation of non-fake content into fake news, and vice versa.File in questo prodotto:
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