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International Conference on Practical Applications of Computational Biology & Bioinformatics

PACBB 2020: Practical Applications of Computational Biology & Bioinformatics, 14th International Conference (PACBB 2020) pp 102–111Cite as

Machine Learning for Depression Screening in Online Communities

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1240))

Abstract

Social media writings have been explored over the last years, in the context of mental health, as a potential source of information for extending the so-called digital phenotyping of a person. In this paper we present a computational approach for the classification of depressed social media users. We conducted a cross evaluation study based on two public datasets, collected from the same social network, in order to understand the impact of transfer learning when the data source is virtually the same. We hope that the results presented here challenge the research community to address more often the issues of reproducibility and interoperability, two key concepts in the era of computational Big Data.

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Notes

  1. 1.

    https://www.twitter.com/.

  2. 2.

    https://www.reddit.com/.

  3. 3.

    https://gist.github.com/sebleier/554280.

  4. 4.

    www.python.org.

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Acknowledgements

This work was supported by the Integrated Programme of SR&TD SOCA (Ref. CENTRO-01-0145-FEDER-000010), co-funded by Centro 2020 program, Portugal 2020, European Union, through the European Regional Development Fund. Rui Antunes is supported by the Fundação para a Ciência e a Tecnologia (PhD Grant SFRH/BD/137000/2018).

Author information

Authors and Affiliations

  1. DETI/IEETA, University of Aveiro, Aveiro, Portugal

    Alina Trifan, Rui Antunes & José Luís Oliveira

Authors
  1. Alina Trifan
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  2. Rui Antunes
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  3. José Luís Oliveira
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Corresponding author

Correspondence to Alina Trifan .

Editor information

Editors and Affiliations

  1. Enhanced Regenerative Medicine, Istituto Italiano di Tecnologia, Genoa, Genova, Italy

    Gabriella Panuccio

  2. Department de Informática, Universidade do Minho, Braga, Portugal

    Miguel Rocha

  3. Computer Science Department, University of Vigo, Vigo, Spain

    Florentino Fdez-Riverola

  4. Institute for Artificial Intelligence and Big Data (AIBIG), Universiti Malaysia Kelantan, Kampus Kota, Kota Bharu, Malaysia

    Mohd Saberi Mohamad

  5. Biotechnology, Intelligent Systems and Educational Technology (BISITE) Research Group, University of Salamanca, Salamanca, Salamanca, Spain

    Roberto Casado-Vara

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Trifan, A., Antunes, R., Oliveira, J.L. (2021). Machine Learning for Depression Screening in Online Communities. In: Panuccio, G., Rocha, M., Fdez-Riverola, F., Mohamad, M., Casado-Vara, R. (eds) Practical Applications of Computational Biology & Bioinformatics, 14th International Conference (PACBB 2020). PACBB 2020. Advances in Intelligent Systems and Computing, vol 1240. Springer, Cham. https://doi.org/10.1007/978-3-030-54568-0_11

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