@inproceedings{szabo-etal-2016-hungarian,
title = "A {H}ungarian Sentiment Corpus Manually Annotated at Aspect Level",
author = "Szab{\'o}, Martina Katalin and
Vincze, Veronika and
Simk{\'o}, Katalin Ilona and
Varga, Viktor and
Hangya, Viktor",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1459",
pages = "2873--2878",
abstract = "In this paper we present a Hungarian sentiment corpus manually annotated at aspect level. Our corpus consists of Hungarian opinion texts written about different types of products. The main aim of creating the corpus was to produce an appropriate database providing possibilities for developing text mining software tools. The corpus is a unique Hungarian database: to the best of our knowledge, no digitized Hungarian sentiment corpus that is annotated on the level of fragments and targets has been made so far. In addition, many language elements of the corpus, relevant from the point of view of sentiment analysis, got distinct types of tags in the annotation. In this paper, on the one hand, we present the method of annotation, and we discuss the difficulties concerning text annotation process. On the other hand, we provide some quantitative and qualitative data on the corpus. We conclude with a description of the applicability of the corpus.",
}
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%0 Conference Proceedings
%T A Hungarian Sentiment Corpus Manually Annotated at Aspect Level
%A Szabó, Martina Katalin
%A Vincze, Veronika
%A Simkó, Katalin Ilona
%A Varga, Viktor
%A Hangya, Viktor
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F szabo-etal-2016-hungarian
%X In this paper we present a Hungarian sentiment corpus manually annotated at aspect level. Our corpus consists of Hungarian opinion texts written about different types of products. The main aim of creating the corpus was to produce an appropriate database providing possibilities for developing text mining software tools. The corpus is a unique Hungarian database: to the best of our knowledge, no digitized Hungarian sentiment corpus that is annotated on the level of fragments and targets has been made so far. In addition, many language elements of the corpus, relevant from the point of view of sentiment analysis, got distinct types of tags in the annotation. In this paper, on the one hand, we present the method of annotation, and we discuss the difficulties concerning text annotation process. On the other hand, we provide some quantitative and qualitative data on the corpus. We conclude with a description of the applicability of the corpus.
%U https://aclanthology.org/L16-1459
%P 2873-2878
Markdown (Informal)
[A Hungarian Sentiment Corpus Manually Annotated at Aspect Level](https://aclanthology.org/L16-1459) (Szabó et al., LREC 2016)
ACL
- Martina Katalin Szabó, Veronika Vincze, Katalin Ilona Simkó, Viktor Varga, and Viktor Hangya. 2016. A Hungarian Sentiment Corpus Manually Annotated at Aspect Level. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2873–2878, Portorož, Slovenia. European Language Resources Association (ELRA).