Identificación del sentimiento expresado usando redes sociales en un contexto político

Translated title of the contribution: Identification of the sentiment expressed using social networks in a political context

Victor W. Bohorquez Lopez, Christiam Mendez Lazarte, Lucas Altube, Enmanuel Santana

Research output: Contribution to conferencePaper (Contribution to a conference)peer-review

1 Scopus citations

Abstract

This study aims to propose a solution to the problem of identifying the feeling of comments in Spanish, due to the linguistic variations existing in the different Latin American countries, expressed in social networks using as an example a political context of an Argentinian Province. To achieve this, a combination of an unsupervised machine-learning algorithm was used to do the pseudo classification, with a supervised machine-learning algorithm, for the classification model. The results show that the level of accuracy obtained is 93%, which is higher than the levels of accuracy found in previous studies. Among the contributions of the study, we can highlight the need to include a layer of pre-processing, to correct spelling errors and reduce vectorization by generating a classifier with greater precision; and a pseudo-classification process, as an alternative to manually classifying thousands of comments to achieve a dataset for training a classifier.

Translated title of the contributionIdentification of the sentiment expressed using social networks in a political context
Original languageSpanish
StatePublished - 2019
Event25th Americas Conference on Information Systems, AMCIS 2019 - Cancun, Mexico
Duration: 15 Aug 201917 Aug 2019

Conference

Conference25th Americas Conference on Information Systems, AMCIS 2019
Country/TerritoryMexico
CityCancun
Period15/08/1917/08/19

COAR

  • Conference Object

Ulima Repository Category

  • Ciencias sociales / Política

Ulima Repository Subject

  • Argentina
  • Emociones
  • Emotions
  • Online social networks
  • Opinión pública
  • Public opinion
  • Redes sociales en Internet

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