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News Article Classification of Mexican Newspapers

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Telematics and Computing (WITCOM 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 944))

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Abstract

Articles in newspapers are divided in sections like culture, politics and sports to help readers to find information easily. Newspapers editors read the articles and decide the ones to be published and the sections they belong to. This paper presents supervised machine learning methods to automatically classify news articles in newspaper sections. To perform this task 4,027 news articles were collected along with its corresponding sections from three Mexican newspapers during a six month period. Different features were extracted and several machine learning methods were tested. Obtained results show an accuracy over 80% classifying articles in the particular sections of the three selected newspapers.

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Notes

  1. 1.

    http://www.eluniversal.com.mx/.

  2. 2.

    http://www.excelsior.com.mx/.

  3. 3.

    http://www.jornada.com.mx.

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Acknowledgments

We thank the support of Insituto Politécnico Nacional (IPN), ESCOM-IPN, SIP-IPN projects numbers: 20181102, 20180859, COFAA-IPN and EDI-IPN.

Author information

Authors and Affiliations

  1. Instituto Politécnico Nacional, ESCOM, Lindavista, G.A. Madero, Mexico City, 07738, Mexico

    Consuelo-Varinia García-Mendoza & Omar Gambino Juárez

Authors
  1. Consuelo-Varinia García-Mendoza
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  2. Omar Gambino Juárez
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Corresponding author

Correspondence to Omar Gambino Juárez .

Editor information

Editors and Affiliations

  1. UPIITA-IPN, México, Mexico

    Miguel Felix Mata-Rivera

  2. UPIITA-IPN, México, Mexico

    Roberto Zagal-Flores

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García-Mendoza, CV., Gambino Juárez, O. (2018). News Article Classification of Mexican Newspapers. In: Mata-Rivera, M., Zagal-Flores, R. (eds) Telematics and Computing . WITCOM 2018. Communications in Computer and Information Science, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-03763-5_9

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  • DOI: https://doi.org/10.1007/978-3-030-03763-5_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03762-8

  • Online ISBN: 978-3-030-03763-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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