@inproceedings{kocon-etal-2018-context,
title = "Context-sensitive Sentiment Propagation in {W}ord{N}et",
author = "Koco{\'n}, Jan and
Janz, Arkadiusz and
Piasecki, Maciej",
editor = "Bond, Francis and
Vossen, Piek and
Fellbaum, Christiane",
booktitle = "Proceedings of the 9th Global Wordnet Conference",
month = jan,
year = "2018",
address = "Nanyang Technological University (NTU), Singapore",
publisher = "Global Wordnet Association",
url = "https://aclanthology.org/2018.gwc-1.39",
pages = "329--334",
abstract = "In this paper we present a comprehensive overview of recent methods of the sentiment propagation in a wordnet. Next, we propose a fully automated method called Classifier-based Polarity Propagation, which utilises a very rich set of features, where most of them are based on wordnet relation types, multi-level bag-of-synsets and bag-of-polarities. We have evaluated our solution using manually annotated part of plWordNet 3.1 emo, which contains more than 83k manual sentiment annotations, covering more than 41k synsets. We have demonstrated that in comparison to existing rule-based methods using a specific narrow set of semantic relations our method has achieved statistically significant and better results starting with the same seed synsets.",
}
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%0 Conference Proceedings
%T Context-sensitive Sentiment Propagation in WordNet
%A Kocoń, Jan
%A Janz, Arkadiusz
%A Piasecki, Maciej
%Y Bond, Francis
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 9th Global Wordnet Conference
%D 2018
%8 January
%I Global Wordnet Association
%C Nanyang Technological University (NTU), Singapore
%F kocon-etal-2018-context
%X In this paper we present a comprehensive overview of recent methods of the sentiment propagation in a wordnet. Next, we propose a fully automated method called Classifier-based Polarity Propagation, which utilises a very rich set of features, where most of them are based on wordnet relation types, multi-level bag-of-synsets and bag-of-polarities. We have evaluated our solution using manually annotated part of plWordNet 3.1 emo, which contains more than 83k manual sentiment annotations, covering more than 41k synsets. We have demonstrated that in comparison to existing rule-based methods using a specific narrow set of semantic relations our method has achieved statistically significant and better results starting with the same seed synsets.
%U https://aclanthology.org/2018.gwc-1.39
%P 329-334
Markdown (Informal)
[Context-sensitive Sentiment Propagation in WordNet](https://aclanthology.org/2018.gwc-1.39) (Kocoń et al., GWC 2018)
ACL
- Jan Kocoń, Arkadiusz Janz, and Maciej Piasecki. 2018. Context-sensitive Sentiment Propagation in WordNet. In Proceedings of the 9th Global Wordnet Conference, pages 329–334, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.