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International Conference on Technologies and Innovation

CITI 2019: Technologies and Innovation pp 81–94Cite as

Mining Twitter for Measuring Social Perception Towards Diabetes and Obesity in Central America

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1124))

Abstract

For a long time, diabetes and obesity have been considered a menace only in developed countries. Nevertheless, the proliferation of unhealthy habits, such as fast-food chains and sedentary lifestyles, have caused diabetes and obesity to spread worldwide causing many and costly complications. Since citizens use of the Internet to search, learn, and share their daily personal experiences, the social networks have become popular data-sources that facilitate a deeper understanding of public health concerns. However, the exploitation of this data requires labelled resources and examples; however, as far as our knowledge, these resources do not exist in Spanish. Consequently, (1) we compile a balanced multi-class corpus with tweets regarding diabetes and obesity written in Spanish in Central-America; and, (2) we use the aforementioned corpus to train and test a machine-learning classifier capable of determining whether the texts related to diabetes or obesity are positive, negative, or neutral. The experimental results show that the best result was obtained through the Bag of Words model with an accuracy of 84.30% with the LIBLinear library. As a final contribution, the compiled corpus is released.

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Notes

  1. 1.

    https://www.who.int/news-room/fact-sheets/detail/diabetes.

  2. 2.

    https://developer.twitter.com/en/docs/tweets/search/overview/standard.

  3. 3.

    https://semantics.inf.um.es/joseagd/diabetes-and-obesity-positive-neutral-negative.rar.

  4. 4.

    https://developer.twitter.com/en/developer-terms/more-on-restricted-use-cases.

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Acknowledgements

This work has been supported by the Spanish National Research Agency (AEI) and the European Regional Development Fund (FEDER/ERDF) through project KBS4FIA (TIN2016-76323-R).

Author information

Authors and Affiliations

  1. Facultad de Ciencias Matemáticas y Físicas, Universidad de Guayaquil, Cdla. Universitaria Salvador Allende, Guayaquil, 090514, Ecuador

    José Medina-Moreira, Oscar Apolinardo-Arzube & Harry Luna-Aveiga

  2. Facultad de Informática, Universidad de Murcia, Campus de Espinardo, 30100, Murcia, Spain

    José Antonio García-Díaz & Rafael Valencia-García

Authors
  1. José Medina-Moreira
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  2. José Antonio García-Díaz
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  3. Oscar Apolinardo-Arzube
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  4. Harry Luna-Aveiga
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  5. Rafael Valencia-García
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Corresponding author

Correspondence to José Antonio García-Díaz .

Editor information

Editors and Affiliations

  1. Universidad de Murcia, Murcia, Spain

    Rafael Valencia-García

  2. Universidad de Castilla la Mancha, Toledo, Spain

    Gema Alcaraz-Mármol

  3. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Javier Del Cioppo-Morstadt

  4. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Néstor Vera-Lucio

  5. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Martha Bucaram-Leverone

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Medina-Moreira, J., García-Díaz, J.A., Apolinardo-Arzube, O., Luna-Aveiga, H., Valencia-García, R. (2019). Mining Twitter for Measuring Social Perception Towards Diabetes and Obesity in Central America. In: Valencia-García, R., Alcaraz-Mármol, G., Del Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) Technologies and Innovation. CITI 2019. Communications in Computer and Information Science, vol 1124. Springer, Cham. https://doi.org/10.1007/978-3-030-34989-9_7

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  • DOI: https://doi.org/10.1007/978-3-030-34989-9_7

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  • Online ISBN: 978-3-030-34989-9

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