A lexicon-enhanced method for sentiment classification: An experiment on online product reviews

Yan Dang; Yulei Zhang; Hsinchun Chen

doi:10.1109/MIS.2009.105

A lexicon-enhanced method for sentiment classification: An experiment on online product reviews

Yan Dang, Yulei Zhang, Hsinchun Chen

Business, The W.A. Franke College of (CoB)

Research output: Contribution to journal › Article › peer-review

221 Scopus citations

Abstract

A proposed lexicon-enhanced method for sentiment classification combines machine-learning and semantic-orientation approaches into one framework that significantly improves sentiment-classification performance.

Original language	English (US)
Article number	5339128
Pages (from-to)	46-53
Number of pages	8
Journal	IEEE Intelligent Systems
Volume	25
Issue number	4
DOIs	https://doi.org/10.1109/MIS.2009.105
State	Published - 2010

ASJC Scopus subject areas

Computer Networks and Communications
Artificial Intelligence

Access to Document

10.1109/MIS.2009.105

Cite this

@article{41ed0b2d8b3e413190039dd0e74132ad,

title = "A lexicon-enhanced method for sentiment classification: An experiment on online product reviews",

abstract = "A proposed lexicon-enhanced method for sentiment classification combines machine-learning and semantic-orientation approaches into one framework that significantly improves sentiment-classification performance.",

author = "Yan Dang and Yulei Zhang and Hsinchun Chen",

note = "Funding Information: This work was supported by the US National Science Foundation{\textquoteright}s Computer and Network Systems (CNS) Program, under grant number CNS-0709338, between September 2007 and August 2010.",

year = "2010",

doi = "10.1109/MIS.2009.105",

language = "English (US)",

volume = "25",

pages = "46--53",

journal = "IEEE Intelligent Systems",

issn = "1541-1672",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - A lexicon-enhanced method for sentiment classification

T2 - An experiment on online product reviews

AU - Dang, Yan

AU - Zhang, Yulei

AU - Chen, Hsinchun

N1 - Funding Information: This work was supported by the US National Science Foundation’s Computer and Network Systems (CNS) Program, under grant number CNS-0709338, between September 2007 and August 2010.

PY - 2010

Y1 - 2010

N2 - A proposed lexicon-enhanced method for sentiment classification combines machine-learning and semantic-orientation approaches into one framework that significantly improves sentiment-classification performance.

AB - A proposed lexicon-enhanced method for sentiment classification combines machine-learning and semantic-orientation approaches into one framework that significantly improves sentiment-classification performance.

UR - https://www.scopus.com/pages/publications/78349268014

UR - https://www.scopus.com/inward/citedby.url?scp=78349268014&partnerID=8YFLogxK

U2 - 10.1109/MIS.2009.105

DO - 10.1109/MIS.2009.105

M3 - Article

AN - SCOPUS:78349268014

SN - 1541-1672

VL - 25

SP - 46

EP - 53

JO - IEEE Intelligent Systems

JF - IEEE Intelligent Systems

IS - 4

M1 - 5339128

ER -

A lexicon-enhanced method for sentiment classification: An experiment on online product reviews

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this