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Rude waiter but mouthwatering pastries! An exploratory study into Dutch aspect-based sentiment analysis

Orphée De Clercq (UGent) and Veronique Hoste (UGent)
(2016) LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION. p.2910-2917
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Abstract
The fine-grained task of automatically detecting all sentiment expressions within a given document and the aspects to which they refer is known as aspect-based sentiment analysis. In this paper we present the first full aspect-based sentiment analysis pipeline for Dutch and apply it to customer reviews. To this purpose, we collected reviews from two different domains, i.e. restaurant and smartphone reviews. Both corpora have been manually annotated using newly developed guidelines that comply to standard practices in the field. For our experimental pipeline we perceive aspect-based sentiment analysis as a task consisting of three main subtasks which have to be tackled incrementally: aspect term extraction, aspect category classification and polarity classification. First experiments on our Dutch restaurant corpus reveal that this is indeed a feasible approach that yields promising results.
Keywords
LT3, aspect-based sentiment analysis, user-generated content, semantic processing

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MLA
De Clercq, Orphée, and Veronique Hoste. “Rude Waiter but Mouthwatering Pastries! An Exploratory Study into Dutch Aspect-Based Sentiment Analysis.” LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, edited by Nicoletta Calzolari et al., ELRA, 2016, pp. 2910–17.
APA
De Clercq, O., & Hoste, V. (2016). Rude waiter but mouthwatering pastries! An exploratory study into Dutch aspect-based sentiment analysis. In N. Calzolari, K. Choukri, T. Declerck, S. Goggi, M. Grobelnik, B. Maegaard, … S. Piperidis (Eds.), LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (pp. 2910–2917). ELRA.
Chicago author-date
De Clercq, Orphée, and Veronique Hoste. 2016. “Rude Waiter but Mouthwatering Pastries! An Exploratory Study into Dutch Aspect-Based Sentiment Analysis.” In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, edited by Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, S. Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, et al., 2910–17. ELRA.
Chicago author-date (all authors)
De Clercq, Orphée, and Veronique Hoste. 2016. “Rude Waiter but Mouthwatering Pastries! An Exploratory Study into Dutch Aspect-Based Sentiment Analysis.” In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, ed by. Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, S. Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, H. Mazo, Asuncion Moreno, Jan Odijk, and Stelios Piperidis, 2910–2917. ELRA.
Vancouver
1.
De Clercq O, Hoste V. Rude waiter but mouthwatering pastries! An exploratory study into Dutch aspect-based sentiment analysis. In: Calzolari N, Choukri K, Declerck T, Goggi S, Grobelnik M, Maegaard B, et al., editors. LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION. ELRA; 2016. p. 2910–7.
IEEE
[1]
O. De Clercq and V. Hoste, “Rude waiter but mouthwatering pastries! An exploratory study into Dutch aspect-based sentiment analysis,” in LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, Portoroz, SLOVENIA, 2016, pp. 2910–2917.
@inproceedings{8630455,
  abstract     = {{The fine-grained task of automatically detecting all sentiment expressions within a given document and the aspects to which they refer is known as aspect-based sentiment analysis. In this paper we present the first full aspect-based sentiment analysis pipeline for Dutch
and apply it to customer reviews. To this purpose, we collected reviews from two different domains, i.e. restaurant and smartphone reviews. Both corpora have been manually annotated using newly developed guidelines that comply to standard practices in the field. For our experimental pipeline we perceive aspect-based sentiment analysis as a task consisting of three main subtasks which have to be tackled incrementally: aspect term extraction, aspect category classification and polarity classification. First experiments on our Dutch restaurant corpus reveal that this is indeed a feasible approach that yields promising results.}},
  author       = {{De Clercq, Orphée and Hoste, Veronique}},
  booktitle    = {{LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION}},
  editor       = {{Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Goggi, S. and Grobelnik, Marko and Maegaard, Bente and Mariani, Joseph and Mazo, H. and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios}},
  isbn         = {{9782951740891}},
  keywords     = {{LT3,aspect-based sentiment analysis,user-generated content,semantic processing}},
  language     = {{eng}},
  location     = {{Portoroz, SLOVENIA}},
  pages        = {{2910--2917}},
  publisher    = {{ELRA}},
  title        = {{Rude waiter but mouthwatering pastries! An exploratory study into Dutch aspect-based sentiment analysis}},
  url          = {{http://www.lrec-conf.org/proceedings/lrec2016/pdf/63_Paper.pdf}},
  year         = {{2016}},
}
Web of Science
Times cited: