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Creating an Annotated Corpus for Aspect-Based Sentiment Analysis in Swedish

Conference paper
Authors Jacobo Rouces
Lars Borin
Nina Tahmasebi
Published in Proceedings of the 5th conference in Digital Humanities in the Nordic Countries
ISSN 1613-0073
Publication year 2020
Published at Department of Swedish
Language en
Links https://gup.ub.gu.se/file/208068
Keywords Aspect-Based Sentiment Analysis, Swedish, Sentiment Gold Standard, Sentiment Annotation
Subject categories Computational linguistics

Abstract

Aspect-Based Sentiment Analysis constitutes a more fine-grained alternative to traditional sentiment analysis at sentence level. In addition to a sentiment value denoting how positive or negative a particular opinion or sentiment expression is, it identifies additional aspects or 'slots' that characterize the opinion. Some typical aspects are target and source, i.e. who holds the opinion and about which entity or aspect is the opinion. We present a large Swedish corpus annotated for Aspect-Based Sentiment Analysis. Each sentiment expression is annotated as a tuple that contains the following fields: one among 5 possible sentiment values, the target, the source, and whether the sentiment expressed is ironic. In addition, the linguistic element that conveys the sentiment is identified too. Sentiment for a particular topic is also annotated at title, paragraph and document level. The documents are articles obtained from two Swedish media (Svenska Dagbladet and Aftonbladet) and one online forum (Flashback), totalling around 4000 documents. The corpus is freely available and we plan to use it for training and testing an Aspect-Based Sentiment Analysis system.

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