A Sentiment Analysis Classification Approach to Assess the Emotional Content of Photographs

Abstract

The integration of Ambient Intelligence and Sentiment Analysis provides mutual benefits. On the one hand, Sentiment Analysis may enable developing interfaces providing a more natural interaction with human-computer interfaces. On the other, AmI enables using context-awareness information to enhance the performance of the system, achieving a more efficient and proactive human-machine communication that can be dynamically adapted to the user’s state and the status of the environment. In this paper, we describe a novel Sentiment Analysis approach combining a lexicon-based model for specifying the set of emotions and a statistical methodology to identify the most relevant topics in the document that are the targets of the sentiments. Our proposal also includes an heuristic learning method that allows improving the initial knowledge considering the users’ feedback. We have integrated the proposed Sentiment Analysis approach into an Android-based mobile App that automatically assigns sentiments to pictures taking into account the description provided by the users.