Onyx: A Linked Data approach to emotion representation

Sánchez Rada, Juan Fernando and Iglesias Fernandez, Carlos Angel (2015). Onyx: A Linked Data approach to emotion representation. "Information Processing & Management" ; pp. 1-24. ISSN 0306-4573. https://doi.org/10.1016/j.ipm.2015.03.007.


Title: Onyx: A Linked Data approach to emotion representation
  • Sánchez Rada, Juan Fernando
  • Iglesias Fernandez, Carlos Angel
Item Type: Article
Título de Revista/Publicación: Information Processing & Management
Date: March 2015
ISSN: 0306-4573
Freetext Keywords: Emotion analysis, ontology, provenance, Linked Data, EmotionML, lexical resources
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is 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. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on 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 the Lexicon Model for Ontologies (lemon), a 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 this work, Onyx has been aligned with EmotionML and WordNet-Affect.

Funding Projects

FP7296277EUROSENTIMENTPARADIGMA TECNOLOGICO SLLanguage Resource Pool for Sentiment Analysis in European Languages

More information

Item ID: 37389
DC Identifier: https://oa.upm.es/37389/
OAI Identifier: oai:oa.upm.es:37389
DOI: 10.1016/j.ipm.2015.03.007
Official URL: http://www.sciencedirect.com/science/article/pii/S030645731500045X
Deposited by: Memoria Investigacion
Deposited on: 07 Sep 2015 17:07
Last Modified: 31 May 2019 17:27
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