Place of publication:

Proceedings of the 10th Global Wordnet Conference

Title:

Propagation of emotions, arousal and polarity in WordNet using Heterogeneous Structured Synset Embeddings

Authors:

Jan Kocoń, Arkadiusz Janz

Abstract:

In this paper we present a novel method for emotive propagation in a wordnet based on a large emotive seed. We introduce a sense-level emotive lexicon annotated with polarity, arousal and emotions. The data were annotated as a part of a large study involving over 20,000 participants. A total of 30,000 lexical units in Polish WordNet were described with metadata, each unit received about 50 annotations concerning polarity, arousal and 8 basic emotions, marked on a multilevel scale. We present a preliminary approach to propagating emotive metadata to unlabeled lexical units based on the distribution of manual annotations using logistic regression and description of mixed synset embeddings based on our Heterogeneous Structured Synset Embeddings.

Link: ACL Anthology

Citation BibTeX:

@inproceedings{kocon-janz-2019-propagation,
title = “Propagation of emotions, arousal and polarity in {W}ord{N}et using Heterogeneous Structured Synset Embeddings”,
author = “Koco{\’n}, Jan and
Janz, Arkadiusz”,
booktitle = “Proceedings of the 10th Global Wordnet Conference”,
month = jul,
year = “2019”,
address = “Wroclaw, Poland”,
publisher = “Global Wordnet Association”,
url = “https://www.aclweb.org/anthology/2019.gwc-1.43”,
pages = “336–341”,
abstract = “In this paper we present a novel method for emotive propagation in a wordnet based on a large emotive seed. We introduce a sense-level emotive lexicon annotated with polarity, arousal and emotions. The data were annotated as a part of a large study involving over 20,000 participants. A total of 30,000 lexical units in Polish WordNet were described with metadata, each unit received about 50 annotations concerning polarity, arousal and 8 basic emotions, marked on a multilevel scale. We present a preliminary approach to propagating emotive metadata to unlabeled lexical units based on the distribution of manual annotations using logistic regression and description of mixed synset embeddings based on our Heterogeneous Structured Synset Embeddings.”,
}