Sentribute: Image Sentiment Analysis from a Mid-level ...

sentribute : Image Sentiment Analysis from a Mid-levelPerspectiveJianbo YuanDepartment of Electrical & ComputerEngineeringUniversity of RochesterRochester, NY YouDepartment of Computer ScienceUniversity of RochesterRochester, NY McdonoughDepartment of Electrical & ComputerEngineeringUniversity of RochesterRochester, NY LuoDepartment of Computer ScienceUniversity of RochesterRochester, NY content Analysis has always been important yet chal-lenging. Thanks to the popularity of social networks, im-ages become an convenient carrier for information di usionamong online users. To understand the di usion patternsand di erent aspects of the social images, we need to inter-pret the images first. Similar to textual content, images alsocarry di erent levels of Sentiment to their viewers. However,di erent from text, where Sentiment Analysis can use easilyaccessible semantic and context information, how to extractand interpret the Sentiment of an Image remains quite chal-lenging. In this paper, we propose an Image Sentiment pre-diction framework, which leverages the Mid-level attributesof an Image to predict its Sentiment .

Figure 1: Selected images crawled from Twitter showing (left column) positive sentiment and (right column) negative sentiments. Semantics and concept learning approaches [6, 19, 16, 22]

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  Form, Analysis, Image, Sentiment, Sentribute, Image sentiment analysis from

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