STORRE: Multilingual Sentiment Analysis: State of the Art and ... [PDF]

dc.relation, Dashtipour K, Poria S, Hussain A, Cambria E, Hawalah AYA, Gelbukh A & Zhou Q (2016) Multilingual Sentim

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STORRE STORRE: Stirling Online Research Repository STORRE (/) / Faculty of Natural Sciences (/handle/1893/2670) / Computing Science and Mathematics (/handle/1893/35) / Computing Science and Mathematics Journal Articles (/handle/1893/216)

Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23283 0

(https://www.altmetric.com/details.php?domain=dspace.stir.ac.uk&citation_id=8829405)

Full metadata record DC Field

Value

Language

dc.contributor.author

Dashtipour, Kia

-

dc.contributor.author

Poria, Soujanya

-

dc.contributor.author

Hussain, Amir

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dc.contributor.author

Cambria, Erik

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dc.contributor.author

Hawalah, Ahmad Y A

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dc.contributor.author

Gelbukh, Alexander

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dc.contributor.author

Zhou, Qiang

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dc.date.accessioned

2017-11-10T03:26:32Z

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dc.date.available

2017-11-10T03:26:32Z

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dc.date.issued

2016-08

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dc.identifier.uri

http://hdl.handle.net/1893/23283

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dc.description.abstract

With the advent of Internet, people actively express their opinions about products, services, events, political parties, etc., in social media, blogs, and website comments. The amount of research work on sentiment analysis is growing explosively. However, the majority of research efforts are devoted to English-language data, while a great share of information is available in other languages. We present a state-of-the-art review on multilingual sentiment analysis. More importantly, we compare our own implementation of existing approaches on common data. Precision observed in our experiments is typically lower than the one reported by the original authors, which we attribute to the lack of detail in the original presentation of those approaches. Thus, we compare the existing works by what they really offer to the reader, including whether they allow for accurate implementation and for reliable reproduction of the reported results.

en_UK

dc.language.iso

en

-

dc.publisher

Springer

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dc.relation

Dashtipour K, Poria S, Hussain A, Cambria E, Hawalah AYA, Gelbukh A & Zhou Q (2016) Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques, Cognitive Computation, 8 (4), pp. 757-771.

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dc.rights

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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dc.subject

Artificial intelligence

en_UK

dc.subject

Natural language processing

en_UK

dc.subject

Opinion mining

en_UK

dc.subject

Sentic computing

en_UK

dc.subject

Sentiment Analysis

en_UK

dc.title

Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques

en_UK

dc.type

Journal Article

en_UK

dc.identifier.doi

http://dx.doi.org/10.1007/s12559-016-9415-7

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dc.citation.jtitle

Cognitive Computation

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dc.citation.issn

1866-9956

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dc.citation.volume

8

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dc.citation.issue

4

-

dc.citation.spage

757

-

dc.citation.epage

771

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dc.citation.publicationstatus

Published

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dc.citation.peerreviewed

Refereed

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dc.type.status

Publisher version (final published refereed version)

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dc.author.email

[email protected]

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dc.citation.date

01/06/2016

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dc.contributor.affiliation

Computing Science - CSM Dept

-

dc.contributor.affiliation

Nanyang Technological University

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dc.contributor.affiliation

Computing Science - CSM Dept

-

dc.contributor.affiliation

Nanyang Technological University

-

dc.contributor.affiliation

Taibah University

-

dc.contributor.affiliation

National Polytechnic Institute

-

dc.contributor.affiliation

Tsinghua University

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dc.identifier.isi

000382169800017

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Appears in Collections:

Computing Science and Mathematics Journal Articles (/handle/1893/216)

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