A linked data approach to sentiment and emotion analysis of twitter in the financial domain

Sánchez Rada, Juan Fernando and Torres, Marcos and Iglesias Fernandez, Carlos Angel and Maestre Martínez, Roberto and Peinado, Esther (2014). A linked data approach to sentiment and emotion analysis of twitter in the financial domain. In: "2nd International Workshop on Finance and Economics on the Semantic Web (FEOSW 2014)", 25/05/2014 - 29/05/2014, Anissaras, Crete, Greece. pp. 1-12.

Description

Title: A linked data approach to sentiment and emotion analysis of twitter in the financial domain
Author/s:
  • Sánchez Rada, Juan Fernando
  • Torres, Marcos
  • Iglesias Fernandez, Carlos Angel
  • Maestre Martínez, Roberto
  • Peinado, Esther
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2nd International Workshop on Finance and Economics on the Semantic Web (FEOSW 2014)
Event Dates: 25/05/2014 - 29/05/2014
Event Location: Anissaras, Crete, Greece
Title of Book: 2nd International Workshop on Finance and Economics on the Semantic Web (FEOSW 2014)
Date: 2014
Subjects:
Freetext Keywords: Linked data, semantic, finance, sentiment analysis, emotions
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities or providers, and complements existing initiatives such as FIBO. The ap- proach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.

More information

Item ID: 36440
DC Identifier: http://oa.upm.es/36440/
OAI Identifier: oai:oa.upm.es:36440
Official URL: http://nadir.uc3m.es/feosw2014/feosw2014-accepted-papers/feosw2014_paper_1.pdf
Deposited by: Memoria Investigacion
Deposited on: 27 Jul 2015 17:54
Last Modified: 27 Jul 2015 17:54
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