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|Type:||Artigo de evento|
|Title:||The Impact Of Visual Attributes On Online Image Diffusion|
Meira Jr. W.
|Abstract:||Little is known on how visual content affects the popularity on social networks, despite images being now ubiquitous on the Web, and currently accounting for a considerable frac- tion of all content shared. Existing art on image sharing fo- cuses mainly on non-visual attributes. In this work we take a complementary approach, and investigate resharing from a mainly visual perspective. Two sets of visual features are proposed, encoding both aesthetical properties (brightness, contrast, sharpness, etc.), and semantical content (concepts represented by the images). We collected data from a large image-sharing service (Pinterest) and evaluated the predic- tive power of different features on popularity (number of reshares). We found that visual properties have low pre- dictive power compared that of social cues. However, after factoring-out social in uence, visual features show consider- able predictive power, especially for images with higher ex- posure, with over 3:1 accuracy odds when classifying highly exposed images between very popular and unpopular. Copyright © 2014 ACM.|
|Editor:||Association for Computing Machinery|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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