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Analyzing and Predicting Sentiment of Images on the Social Web

Siersdorfer, Stefan, Hare, Jonathon, Minack, Enrico and Deng, Fan (2010) Analyzing and Predicting Sentiment of Images on the Social Web At ACM Multimedia 2010, Italy. 25 - 29 Oct 2010. , pp. 715-718.

Record type: Conference or Workshop Item (Poster)


In this paper we study the connection between sentiment of images expressed in metadata and their visual content in the social photo sharing environment Flickr. To this end, we consider the bag-of-visual words representation as well as the color distribution of images, and make use of the SentiWordNet thesaurus to extract numerical values for their sentiment from accompanying textual metadata. We then perform a discriminative feature analysis based on information theoretic methods, and apply machine learning techniques to predict the sentiment of images. Our large-scale empirical study on a set of over half a million Flickr images shows a considerable correlation between sentiment and visual features, and promising results towards estimating the polarity of sentiment in images.

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Published date: 25 October 2010
Additional Information: Event Dates: 25-29 October 2010
Venue - Dates: ACM Multimedia 2010, Italy, 2010-10-25 - 2010-10-29
Keywords: Color features, Classification, Sentiment Analysis, Automatic Annotation, Visual Terms
Organisations: Web & Internet Science


Local EPrints ID: 271670
ISBN: 978-1-60558-933-6
PURE UUID: 5d74f73a-10df-4562-ae70-8656e2eb975d
ORCID for Jonathon Hare: ORCID iD

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Date deposited: 02 Nov 2010 17:59
Last modified: 18 Jul 2017 06:39

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Author: Stefan Siersdorfer
Author: Jonathon Hare ORCID iD
Author: Enrico Minack
Author: Fan Deng

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