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Knowledge-Based Approaches to Concept-Level Sentiment Analysis

Authors:

Catherine HavasiAuthors Info & Claims

IEEE Intelligent Systems, Volume 28, Issue 2

Pages 12 - 14

https://doi.org/10.1109/MIS.2013.45

Published: 01 March 2013 Publication History

Abstract

The guest editors introduce novel approaches to opinion mining and sentiment analysis that go beyond a mere word-level analysis of text and provide concept-level methods. Such approaches allow a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain.

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D’Aniello GGaeta MLa Rocca I(2022)KnowMIS-ABSA: an overview and a reference model for applications of sentiment analysis and aspect-based sentiment analysisArtificial Intelligence Review10.1007/s10462-021-10134-955:7(5543-5574)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s10462-021-10134-9
Zhang JZhang ALiu DBian Y(2021)Customer preferences extraction for air purifiers based on fine-grained sentiment analysis of online reviewsKnowledge-Based Systems10.1016/j.knosys.2021.107259228:COnline publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1016/j.knosys.2021.107259
Subhashini LLi YZhang JAtukorale AWu Y(2021)Mining and classifying customer reviews: a surveyArtificial Intelligence Review10.1007/s10462-021-09955-554:8(6343-6389)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s10462-021-09955-5
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Index Terms

Knowledge-Based Approaches to Concept-Level Sentiment Analysis
1. Hardware
  1. Power and energy
    1. Power estimation and optimization
      1. Platform power issues

Index terms have been assigned to the content through auto-classification.

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Statistical Approaches to Concept-Level Sentiment Analysis

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Sentiment dictionaries are essential for research in the sentiment analysis field. A two-step method integrates iterative regression and random walk with in-link normalization to build a concept-level sentiment dictionary. The approach uses ConceptNet ...
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Published In

IEEE Intelligent Systems Volume 28, Issue 2

March 2013

103 pages

ISSN:1541-1672

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IEEE Educational Activities Department

United States

Publication History

Published: 01 March 2013

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D’Aniello GGaeta MLa Rocca I(2022)KnowMIS-ABSA: an overview and a reference model for applications of sentiment analysis and aspect-based sentiment analysisArtificial Intelligence Review10.1007/s10462-021-10134-955:7(5543-5574)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s10462-021-10134-9
Zhang JZhang ALiu DBian Y(2021)Customer preferences extraction for air purifiers based on fine-grained sentiment analysis of online reviewsKnowledge-Based Systems10.1016/j.knosys.2021.107259228:COnline publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1016/j.knosys.2021.107259
Subhashini LLi YZhang JAtukorale AWu Y(2021)Mining and classifying customer reviews: a surveyArtificial Intelligence Review10.1007/s10462-021-09955-554:8(6343-6389)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s10462-021-09955-5
Wang XJin DLiu MHe DMusial KDang JZhu WTao DCheng XCui PRundensteiner ECarmel DHe QXu Yu J(2019)Emotional Contagion-Based Social Sentiment Mining in Social Networks by Introducing Network CommunitiesProceedings of the 28th ACM International Conference on Information and Knowledge Management10.1145/3357384.3357941(1763-1772)Online publication date: 3-Nov-2019
https://dl.acm.org/doi/10.1145/3357384.3357941
Arulmurugan RSabarmathi KAnandakumar H(2019)RETRACTED ARTICLE: Classification of sentence level sentiment analysis using cloud machine learning techniquesCluster Computing10.1007/s10586-017-1200-122:Suppl 1(1199-1209)Online publication date: 16-Jan-2019
https://dl.acm.org/doi/10.1007/s10586-017-1200-1
Gaur MKursuncu UAlambo ASheth ADaniulaityte RThirunarayan KPathak JCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)"Let Me Tell You About Your Mental Health!"Proceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3271732(753-762)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3271732
Rojas-Galeano S(2017)On Obstructing Obscenity ObfuscationACM Transactions on the Web10.1145/303296311:2(1-24)Online publication date: 24-Apr-2017
https://dl.acm.org/doi/10.1145/3032963
Hung C(2017)Word of mouth quality classification based on contextual sentiment lexiconsInformation Processing and Management: an International Journal10.1016/j.ipm.2017.02.00753:4(751-763)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1016/j.ipm.2017.02.007
Vilares DAlonso MGmez-Rodrguez C(2017)Supervised sentiment analysis in multilingual environmentsInformation Processing and Management: an International Journal10.1016/j.ipm.2017.01.00453:3(595-607)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.ipm.2017.01.004
Sun SLuo CChen J(2017)A review of natural language processing techniques for opinion mining systemsInformation Fusion10.1016/j.inffus.2016.10.00436:C(10-25)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1016/j.inffus.2016.10.004
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Statistical Approaches to Concept-Level Sentiment Analysis

Building a Concept-Level Sentiment Dictionary Based on Commonsense Knowledge

Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining

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