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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.14659 |
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| _version_ | 1866918149010489344 |
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| author | Peng, Shikang Bainbridge, Wilma A. |
| author_facet | Peng, Shikang Bainbridge, Wilma A. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_14659 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Image memorability predicts social media virality and externally-associated commenting Peng, Shikang Bainbridge, Wilma A. Human-Computer Interaction Computational Engineering, Finance, and Science Social and Information Networks J.4 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. |
| title | Image memorability predicts social media virality and externally-associated commenting |
| topic | Human-Computer Interaction Computational Engineering, Finance, and Science Social and Information Networks J.4 |
| url | https://arxiv.org/abs/2409.14659 |