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SentiBank: Large-Scale Ontology and Classifiers for Visual Sentiment Detection

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Published on Oct 6, 2013

We demonstrate a novel system which combines sound structures from psychology and the folksonomy extracted from social multimedia to develop a large visual sentiment ontology consisting of 1,200 concepts and associated classifiers called SentiBank. Each concept, defined as an Adjective Noun Pair (ANP), is made of an adjective strongly indicating emotions and a noun corresponding to objects or scenes that have a reasonable prospect of automatic detection. We demonstrate novel applications made possible by SentiBank including live sentiment prediction of social media and visualization of visual content in a rich intuitive semantic space. For more information, please visit http://www.ee.columbia.edu/dvmm/vso/

paper:
Damian Borth, Rongrong Ji, Tao Chen, Thomas Breuel and Shih-Fu Chang
Large-scale Visual Sentiment Ontology and Detectors Using Adjective Noun Pairs
ACM Int. Conference on Multimedia (ACM MM), Barcelona, Oct 2013.

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