Attention¶
In misinformation contexts, attention refers to the cognitive resources people allocate to evaluating information quality during decision-making. Limited attention—where people fail to sufficiently consider accuracy despite valuing it—is a key mechanism underlying misinformation belief and sharing.
Key insight¶
Misinformation sharing and belief are often not driven by confusion about accuracy or indifference to truth, but by limited attention to accuracy during rapid, real-world decision-making. People care about accuracy in principle but fail to apply that value when deciding what to share due to competing goals (engagement, partisan identity, social bonding) and cognitive constraints.
Key papers¶
- Pennycook et al. (2021) — Shifting attention to accuracy can reduce misinformation online — Foundational paper showing that subtle reminders redirecting attention to accuracy increase accurate news sharing and reduce false news sharing; demonstrates limited attention, not confusion or indifference, as primary driver of misinformation sharing
- Pennycook & Rand (2020) — Fighting COVID-19 Misinformation on Social Media — COVID-19 context application showing that accuracy salience nearly triples truth discernment on sharing tasks
- Ecker et al. (2022) — The psychological drivers of misinformation belief and its resistance to correction — Reviews cognitive mechanisms including limited attention as a factor in continued influence effects
Contrast with related mechanisms¶
- Confusion-based account: People are uncertain about what is true. Attention-based mechanism: People know what is true but don't sufficiently consider it.
- Preference-based account: People don't care about accuracy; they prefer engaging or partisan content. Attention-based mechanism: People value accuracy but attend to other factors first.
Related topics¶
- Behavioral Nudges — interventions that redirect attention
- Psychology of misinformation — cognitive mechanisms in misinformation
- Cognitive reasoning — how analytical thinking relates to accuracy considerations