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Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space

  • Erik Cambria*
  • , Thomas Mazzocco
  • , Amir Hussain
  • , Chris Eckl
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

78 Scopus citations

Abstract

Existing approaches to opinion mining and sentiment analysis mainly rely on parts of text in which opinions and sentiments are explicitly expressed such as polarity terms and affect words. However, opinions and sentiments are often conveyed implicitly through context and domain dependent concepts, which make purely syntactical approaches ineffective. To overcome this problem, we have recently proposed Sentic Computing, a multi-disciplinary approach to opinion mining and sentiment analysis that exploits both computer and social sciences to better recognize and process opinions and sentiments over the Web. Among other tools, Sentic Computing includes AffectiveSpace, a language visualization system that transforms natural language from a linguistic form into a multi-dimensional space. In this work, we present a new technique to better cluster this vector space and, hence, better organize and reason on the affective common sense knowledge in it contained.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011
Pages601-610
Number of pages10
EditionPART 3
DOIs
StatePublished - 2011
Externally publishedYes
Event8th International Symposium on Neural Networks, ISNN 2011 - Guilin, China
Duration: 29 May 20111 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume6677 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Symposium on Neural Networks, ISNN 2011
Country/TerritoryChina
CityGuilin
Period29/05/111/06/11

Keywords

  • AI
  • Clustering
  • NLP
  • Opinion Mining and Sentiment Analysis
  • Semantic Web
  • Sentic Computing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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