@article{onyx15,
author = "S{\'a}nchez-Rada, J. Fernando and Iglesias, Carlos A.",
abstract = "Extracting opinions and emotions from text is becoming more and more important, especially since the advent of micro-blogging and social networking.
Opinion mining has become particularly popular and now gathers many public services, datasets and lexical resources.
Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications.
Some of the barriers for developing such resources are the diversity of emotion theories and the absence of a common vocabulary to express emotion.
This article presents a semantic vocabulary, called Onyx, intended to provide support to represent emotions in lexical resources and emotion analysis services.
It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with lemon, an increasingly popular RDF model for representing lexical entries.
This approach also means a new and interesting way to work with different theories of emotion.
As part of our work, Onyx has been aligned with EmotionML and WordNet-Affect.
",
comments = "JCR 2016 Q2 2.391, SJR 2016 Q2 0.705, Scopus 2016 Q1 5.2 ",
issn = "0306-4573",
journal = "Information Processing {\&} Management",
keywords = "onyx;emotion analysis;linked data",
month = "January",
pages = "99-114",
title = "{O}nyx: {A} {L}inked {D}ata {A}pproach to {E}motion {R}epresentation",
url = "http://www.sciencedirect.com/science/article/pii/S030645731500045X",
volume = "52",
year = "2016",
}