Towards a Common Linked Data Model for Sentiment and Emotion Analysis

J. Fernando Sánchez-Rada, Björn Schuller, Viviana Patti, Paul Buitelaar, Gabriela Vulcu, Felix Bulkhardt et al (2016). Towards a Common Linked Data Model for Sentiment and Emotion Analysis. In J. Fernando Sánchez-Rada & Björn Schuller (editors), Proceedings of the LREC 2016 Workshop Emotion and Sentiment Analysis (ESA 2016), pages 48-54.

Abstract:
The different formats to encode information currently in use in sentiment analysis and opinion mining are heterogeneous and often custom tailored to each application. Besides a number of existing standards, there are additionally still plenty of open challenges, such as representing sentiment and emotion in web services, integration of different models of emotions or linking to other data sources. In this paper, we motivate the switch to a linked data approach in sentiment and emotion analysis that would overcome these and other current limitations. This paper includes a review of the existing approaches and their limitations, an introduction of the elements that would make this change possible, and a discussion of the challenges behind that change.