Negation detection for sentiment analysis: A case study in Spanish

Abstract

<jats:title>Abstract</jats:title> <jats:p>Accurate negation identification is one of the most important tasks in the context of sentiment analysis. In order to correctly interpret the sentiment value of a particular expression, we need to identify whether it is in the scope of negation. While much of the work on negation detection has focused on English, we have seen recent developments that provide accurate identification of negation in other languages. In this paper, we provide an overview of negation detection systems and describe an implementation of a Spanish system for negation cue detection and scope identification. We apply this system to the sentiment analysis task, confirming also for Spanish that improvements can be gained from accurate negation detection. The paper contributes an implementation of negation detection for sentiment analysis in Spanish and a detailed error analysis. This is the first work in Spanish in which a machine learning negation processing system is applied to the sentiment analysis task. Existing methods have used negation rules that have not been assessed, perhaps because the first Spanish corpus annotated with negation for sentiment analysis has only recently become available.</jats:p>

Recent advances in processing negation

“…For Spanish, there have been two editions of the NEGES task (Jiménez-Zafra et al . 2018a; 2019), where systems had to detect negation cues and evaluate the impact of negation in sentiment analysis.…”

A corpus analysis of online news comments using the Appraisal framework

“…The examples in this paragraph are fromMartin and White (2005, p. 100).Cavasso &Taboada (2021). A corpus analysis of online news comments using the Appraisal framework.…”

“…(8) The[brutal] Chinese Communist Party has [murdered] over fifty million of its own people since 1949, since 1999 it has been attempting the [blood-thirsty genocide] of the tens of millions of innocent Falun Gong who live in Mainland China.Cavasso &Taboada (2021). A corpus analysis of online news comments using the Appraisal framework.…”

“…The interface has changed since.9 We used the term 'keyword' to refer to negative items that anchor the negation annotations, not in the technical sense of 'keyword' in corpus linguistics. The former meaning is common in studies of negation and negation annotation for computational purposes(Jiménez-Zafra et al, 2021).Cavasso & Taboada (2021). A corpus analysis of online news comments using the Appraisal framework.…”

Processing negation: An introduction to the special issue

“…These six articles can be grouped based on two criteria: the languages they work with and whether they process negation in order to improve some application. Three articles work with English texts (Schulder, Wiegand, and Ruppenhofer 2020;Barnes, Velldal, and Øvrelid 2020;Sykes et al 2020), and three articles work with texts in other languages: Spanish (Jiménez-Zafra et al 2020;Taul et al 2020), and French and Brazilian Portuguese (Dalloux et al 2020). Regarding applications, three articles present work on processing negation for sentiment analysis (Jiménez-Zafra et al 2020; Schulder et al 2020; Barnes et al 2020), two work in the biomedical domain (Dalloux et al 2020;Sykes et al 2020), and one presents a corpus with focus on negation annotations (Taul et al 2020).…”