Identificación del sentimiento expresado usando redes sociales en un contexto político

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

Resultado de la investigación: Contribución a una conferenciaTexto Científico (Contribución a una conferencia)revisión exhaustiva


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.

Título traducido de la contribuciónIdentification of the sentiment expressed using social networks in a political context
Idioma originalEspañol
EstadoPublicada - 2019
Evento25th Americas Conference on Information Systems, AMCIS 2019 - Cancun, México
Duración: 15 ago. 201917 ago. 2019


Conferencia25th Americas Conference on Information Systems, AMCIS 2019

Palabras Clave

  • Argentina
  • Facebook
  • Political candidates
  • Sentiment analysis
  • Social networks


  • Artículo de conferencia

Categorías Repositorio Ulima

  • Ciencias sociales / Política

Temas Repositorio Ulima

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


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