A Method to Construct Guidelines for Spanish Comments Annotation for Sentiment Analysis

John Urpay-Camasi, Jorge Garcia-Calderon, Pedro Shiguihara

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The application of sentiment analysis in social networks supports the understanding of complaints and claims of users' comments. To train the models that automate this analysis, it is important to construct guidelines that generate a more robust corpus. As far as we know, no related work of guidelines for spanish comments annotation has been found. We propose a method to construct guidelines to annotators reach a consensus in the entire annotation process of spanish comments from social networks. We annotated 3259 spanish comments using our guidelines, where the concordance analysis from our annotators was 84%. We employed our corpus and eight baseline classifiers for sentiment analysis detection, achieving 78.63% as the highest F1-Score with Multilayer Perceptron. Our method is useful to tackle labeling spanish comments which can be used in NLP tasks such as sentiment analysis.

Original languageEnglish
Title of host publicationProceedings of the 2021 IEEE Sciences and Humanities International Research Conference, SHIRCON 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665429146
DOIs
StatePublished - 2021
Externally publishedYes
Event5th IEEE Sciences and Humanities International Research Conference, SHIRCON 2021 - Lima, Peru
Duration: 17 Nov 202119 Nov 2021

Publication series

NameProceedings of the 2021 IEEE Sciences and Humanities International Research Conference, SHIRCON 2021

Conference

Conference5th IEEE Sciences and Humanities International Research Conference, SHIRCON 2021
Country/TerritoryPeru
CityLima
Period17/11/2119/11/21

Keywords

  • annotation of spanish comments
  • dataset labeling
  • guidelines for corpus annotation
  • sentiment analysis

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