Investigation of the use of a multimodal feature learning approach, using neural network based models such as Skip-gram and Denoising Autoencoders, to address sentiment analysis of micro-blogging content, such as Twitter short messages, that are composed by a short text and, possibly, an image.

A multimodal feature learning approach for sentiment analysis of social network multimedia

URICCHIO, TIBERIO;
2016-01-01

Abstract

Investigation of the use of a multimodal feature learning approach, using neural network based models such as Skip-gram and Denoising Autoencoders, to address sentiment analysis of micro-blogging content, such as Twitter short messages, that are composed by a short text and, possibly, an image.
2016
Springer
Internazionale
http://link.springer.com/article/10.1007/s11042-015-2646-x
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11393/313332
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