Image memorability predicts social media virality and externally-associated commenting
September 23, 2024 Β· Declared Dead Β· π Computers in Human Behavior
"No code URL or promise found in abstract"
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Authors
Shikang Peng, Wilma A. Bainbridge
arXiv ID
2409.14659
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CE,
cs.SI
Citations
2
Venue
Computers in Human Behavior
Last Checked
4 months ago
Abstract
Visual content on social media plays a key role in entertainment and information sharing, yet some images gain more engagement than others. We propose that image memorability - the ability to be remembered - may predict viral potential. Using 1,247 Reddit image posts across three timepoints, we assessed memorability with neural network ResMem and correlated the predicted memorability scores with virality metrics. Memorable images were consistently associated with more comments, even after controlling for image categories with ResNet-152. Semantic analysis revealed that memorable images relate to more neutral-affect comments, suggesting a distinct pathway to virality from emotional content. Additionally, visual consistency analysis showed that memorable posts inspired diverse, externally-associated comments. By analyzing ResMem's layers, we found semantic distinctiveness was key to both memorability and virality. This study highlights memorability as a unique correlate of social media virality, offering insights into how visual features and human cognitive behavioral interactions are associated with online engagement.
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