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Canadian Conference on Artificial Intelligence

Canadian AI 2015: Advances in Artificial Intelligence pp 204–211Cite as

Sentiment and Factual Transitions in Online Medical Forums

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9091))

Abstract

This work studies sentiment and factual transitions on an online medical forum where users correspond in English. We work with discussions dedicated to reproductive technologies, an emotionally-charged issue. In several learning problems, we demonstrate that multi-class sentiment classification significantly improves when messages are represented by affective terms combined with sentiment and factual transition information (paired t-test, P=0.0011).

We thank anonymous reviewers for thorough and helpful comments. This work has been supported by NSERC Discovery grant.

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Author information

Authors and Affiliations

  1. Technical University of Moldova, Chisinau, Moldova

    Victoria Bobicev

  2. Institute for Big Data Analytics, Halifax, Canada

    Marina Sokolova

  3. Faculty of Medicine and Faculty of Engineering, University of Ottawa, Ottawa, Canada

    Marina Sokolova

  4. Research Group in Computational Linguistics, University of Wolverhampton, Wolverhampton, UK

    Michael Oakes

Authors
  1. Victoria Bobicev
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  2. Marina Sokolova
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  3. Michael Oakes
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Corresponding author

Correspondence to Marina Sokolova .

Editor information

Editors and Affiliations

  1. University of Alberta, Edmonton, Canada

    Denilson Barbosa

  2. Dalhousie University, Halifax, Canada

    Evangelos Milios

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© 2015 Springer International Publishing Switzerland

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Bobicev, V., Sokolova, M., Oakes, M. (2015). Sentiment and Factual Transitions in Online Medical Forums. In: Barbosa, D., Milios, E. (eds) Advances in Artificial Intelligence. Canadian AI 2015. Lecture Notes in Computer Science(), vol 9091. Springer, Cham. https://doi.org/10.1007/978-3-319-18356-5_18

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  • DOI: https://doi.org/10.1007/978-3-319-18356-5_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18355-8

  • Online ISBN: 978-3-319-18356-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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