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Cited by 71Sentiment Analysis and Opinion MiningComputational and Text Analysis MethodsTopic Modeling

Using rhetorical structure in sentiment analysis

Open access
Hogenboom, Alexander, Frasincar, Flavius, de Jong, Franciska, Kaymak, Uzay·2015·Communications of the ACM
DOI 10.1145/2699418
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Abstract

A deep, fine-grain analysis of rhetorical structure highlights crucial sentiment-carrying text segments.

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Crossref · 10.1145/2699418

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References 27 · Cited by 71

Authors
Hogenboom, A., Frasincar, F., de Jong, F., & Kaymak, U.
Affiliations
  • Erasmus University Rotterdam (NL)
  • Erasmus Research Institute of Management of Erasmus University Rotterdam, the Netherlands
  • University of Twente, the Netherlands
  • Eindhoven University of Technology (NL)
ORCID
Venue
Communications of the ACM
Publisher
Association for Computing Machinery (ACM)
Published
2015-06-25
Volume
58
Issue
7
Pages
69-77
ISSN
  • 0001-0782 (ISSN-L)
  • 1557-7317
DOI
10.1145/2699418
OpenAlex
W1842565584
Cited by
71
References
27
Citations by year
2026: 2 · 2024: 4 · 2023: 2 · 2022: 9 · 2021: 5 · 2020: 10 · 2019: 6 · 2018: 4 · 2017: 16 · 2016: 8 · 2015: 5
FWCI
10.77
Type
journal article
Language
en
Open access
Licence
Locations
  • Communications of the ACM (publishedVersion)
  • TU/e Research Portal (publishedVersion)
  • University of Twente Research Information (publishedVersion, other-oa)
  • TU/e Research Portal (submittedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • University of Twente Research Information (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
Keywords
rhetorical structure, sentiment analysis, Rhetorical Structure Theory

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