Detecting speculations, contrasts and conditionals in consumer reviews

Maria Skeppstedt; Teri Schamp-Bjerede; Magnus Sahlgren; Carita Paradis; Andreas Kerren

Detecting speculations, contrasts and conditionals in consumer reviews

Maria Skeppstedt, Teri Schamp-Bjerede, Magnus Sahlgren, Carita Paradis, Andreas Kerren

Engelska

Gagavai AB

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

A support vector classifier was compared to a lexicon-based approach for the task of detecting the stance categories speculation, contrast and conditional in English consumer reviews. Around 3,000 training instances were required to achieve a stable performance of an F-score of 90 for speculation. This outperformed the lexicon-based approach, for which an Fscore of just above 80 was achieved. The machine learning results for the other two categories showed a lower average (an approximate F-score of 60 for contrast and 70 for conditional), as well as a larger variance, and were only slightly better than lexicon matching. Therefore, while machine learning was successful for detecting speculation, a well-curated lexicon might be a more suitable approach for detecting contrast and conditional.

Originalspråk	engelska
Titel på värdpublikation	6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings
Redaktörer	Balahur Alexandra, van der Goot Erik, Vossen Piek, Montoyo Andrés
Förlag	Association for Computational Linguistics
Sidor	162-168
Antal sidor	7
ISBN (tryckt)	978-1-941643-32-7
Status	Published - 2015
Evenemang	6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA '15) - Lisbon Varaktighet: 2015 sep. 17 → …

Konferens

Konferens	6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA '15)
Period	2015/09/17 → …

Ämnesklassifikation (UKÄ)

Språk och litteratur
Datavetenskap (datalogi)

Tillgång till dokument

http://www.aclweb.org/anthology/W/W15/W15-29.pdf#page.162

StaViCTA - Nya landvinningar inom beskrivning och förklaring av ställningstagande i språklig kommunikation genom metoder från datalogi och informationvisualisering
Paradis, C. (PI), Kerren, A. (PI), Sahlgren, M. (PI), Kucher, K. (Forskare), Skeppstedt, M. (Forskare) & Simaki, V. (PI)
Swedish Research Council
2013/01/01 → 2018/01/02
Projekt: Forskning

Citera det här

Skeppstedt, M., Schamp-Bjerede, T., Sahlgren, M., Paradis, C., & Kerren, A. (2015). Detecting speculations, contrasts and conditionals in consumer reviews. I B. Alexandra, V. D. G. Erik, V. Piek, & M. Andrés (Red.), 6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings (s. 162-168). Association for Computational Linguistics. http://www.aclweb.org/anthology/W/W15/W15-29.pdf#page.162

Skeppstedt, Maria ; Schamp-Bjerede, Teri ; Sahlgren, Magnus et al. / Detecting speculations, contrasts and conditionals in consumer reviews. 6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings. redaktör / Balahur Alexandra ; van der Goot Erik ; Vossen Piek ; Montoyo Andrés. Association for Computational Linguistics, 2015. s. 162-168

@inproceedings{900a4c9b8c5348c086797aef36931455,

title = "Detecting speculations, contrasts and conditionals in consumer reviews",

abstract = "A support vector classifier was compared to a lexicon-based approach for the task of detecting the stance categories speculation, contrast and conditional in English consumer reviews. Around 3,000 training instances were required to achieve a stable performance of an F-score of 90 for speculation. This outperformed the lexicon-based approach, for which an Fscore of just above 80 was achieved. The machine learning results for the other two categories showed a lower average (an approximate F-score of 60 for contrast and 70 for conditional), as well as a larger variance, and were only slightly better than lexicon matching. Therefore, while machine learning was successful for detecting speculation, a well-curated lexicon might be a more suitable approach for detecting contrast and conditional.",

keywords = "consumer reviews, support vector classifier, stance",

author = "Maria Skeppstedt and Teri Schamp-Bjerede and Magnus Sahlgren and Carita Paradis and Andreas Kerren",

year = "2015",

language = "English",

isbn = "978-1-941643-32-7",

pages = "162--168",

editor = "Balahur Alexandra and Erik, {van der Goot} and Vossen Piek and Montoyo Andr{\'e}s",

booktitle = "6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings",

publisher = "Association for Computational Linguistics",

address = "United States",

note = "6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA '15) ; Conference date: 17-09-2015",

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Skeppstedt, M, Schamp-Bjerede, T, Sahlgren, M, Paradis, C & Kerren, A 2015, Detecting speculations, contrasts and conditionals in consumer reviews. i B Alexandra, VDG Erik, V Piek & M Andrés (red), 6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings. Association for Computational Linguistics, s. 162-168, 6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA '15), 2015/09/17. <http://www.aclweb.org/anthology/W/W15/W15-29.pdf#page.162>

Detecting speculations, contrasts and conditionals in consumer reviews. / Skeppstedt, Maria; Schamp-Bjerede, Teri; Sahlgren, Magnus et al.
6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings. red. / Balahur Alexandra; van der Goot Erik; Vossen Piek; Montoyo Andrés. Association for Computational Linguistics, 2015. s. 162-168.

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

T1 - Detecting speculations, contrasts and conditionals in consumer reviews

AU - Skeppstedt, Maria

AU - Schamp-Bjerede, Teri

AU - Sahlgren, Magnus

AU - Paradis, Carita

AU - Kerren, Andreas

PY - 2015

Y1 - 2015

N2 - A support vector classifier was compared to a lexicon-based approach for the task of detecting the stance categories speculation, contrast and conditional in English consumer reviews. Around 3,000 training instances were required to achieve a stable performance of an F-score of 90 for speculation. This outperformed the lexicon-based approach, for which an Fscore of just above 80 was achieved. The machine learning results for the other two categories showed a lower average (an approximate F-score of 60 for contrast and 70 for conditional), as well as a larger variance, and were only slightly better than lexicon matching. Therefore, while machine learning was successful for detecting speculation, a well-curated lexicon might be a more suitable approach for detecting contrast and conditional.

AB - A support vector classifier was compared to a lexicon-based approach for the task of detecting the stance categories speculation, contrast and conditional in English consumer reviews. Around 3,000 training instances were required to achieve a stable performance of an F-score of 90 for speculation. This outperformed the lexicon-based approach, for which an Fscore of just above 80 was achieved. The machine learning results for the other two categories showed a lower average (an approximate F-score of 60 for contrast and 70 for conditional), as well as a larger variance, and were only slightly better than lexicon matching. Therefore, while machine learning was successful for detecting speculation, a well-curated lexicon might be a more suitable approach for detecting contrast and conditional.

KW - consumer reviews

KW - support vector classifier

KW - stance

M3 - Paper in conference proceeding

SN - 978-1-941643-32-7

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EP - 168

BT - 6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings

A2 - Alexandra, Balahur

A2 - Erik, van der Goot

A2 - Piek, Vossen

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PB - Association for Computational Linguistics

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Skeppstedt M, Schamp-Bjerede T, Sahlgren M, Paradis C, Kerren A. Detecting speculations, contrasts and conditionals in consumer reviews. I Alexandra B, Erik VDG, Piek V, Andrés M, redaktörer, 6th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, WASSA 2015 : Workshop proceedings. Association for Computational Linguistics. 2015. s. 162-168

Detecting speculations, contrasts and conditionals in consumer reviews

Sammanfattning

Konferens

Ämnesklassifikation (UKÄ)

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Projekt

StaViCTA - Nya landvinningar inom beskrivning och förklaring av ställningstagande i språklig kommunikation genom metoder från datalogi och informationvisualisering

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