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Language Alternation in Online Communication with Misinformation

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Smart Business: Technology and Data Enabled Innovative Business Models and Practices (WeB 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 403))

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Abstract

Misinformation has attracted widespread research attention owing to the importance and challenges of addressing the problem. Despite the progress in developing computational methods for misinformation detection and identifying psycholinguistic factors and network properties of misinformation, there is a lack of understanding of language alternation in online misinformation communication. This research aims to address the literature gap by answering several key questions regarding language alternation in communicating misinformation online. Based on the analysis of structured and un-structured survey responses, the results of this study show that it is fairly common for speakers of English as a second language to alternate languages in communicating misinformation online. In addition, it identifies the motives and impacts of such behavior. The findings of this study point to a new avenue for addressing the challenges of detecting online misinformation.

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Acknowledgements

This research is partially supported by U.S. National Science Foundation (Award #: SES 1527684). Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of NSF.

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Authors and Affiliations

  1. The University of North Carolina at Charlotte, Charlotte, NC, 28223, USA

    Lina Zhou, Jaewan Lim, Hamad Alsaleh & Dongsong Zhang

  2. St. Cloud State University, St. Cloud, MN, 56301, USA

    Jieyu Wang

Authors
  1. Lina Zhou
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  2. Jaewan Lim
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  3. Hamad Alsaleh
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  4. Jieyu Wang
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  5. Dongsong Zhang
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Corresponding author

Correspondence to Dongsong Zhang .

Editor information

Editors and Affiliations

  1. Baruch College, New York, NY, USA

    Karl R. Lang

  2. Bentley University, Waltham, MA, USA

    Jennifer Xu

  3. Oregon State University, Corvallis, OR, USA

    Bin Zhu

  4. University of Utah, Salt Lake City, UT, USA

    Xiao Liu

  5. University of Illinois, Champaign, IL, USA

    Michael J. Shaw

  6. Georgia Institute of Technology, Atlanta, GA, USA

    Han Zhang

  7. University of Washington, Seattle, WA, USA

    Ming Fan

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Zhou, L., Lim, J., Alsaleh, H., Wang, J., Zhang, D. (2020). Language Alternation in Online Communication with Misinformation. In: Lang, K.R., et al. Smart Business: Technology and Data Enabled Innovative Business Models and Practices. WeB 2019. Lecture Notes in Business Information Processing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-030-67781-7_15

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  • DOI: https://doi.org/10.1007/978-3-030-67781-7_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67780-0

  • Online ISBN: 978-3-030-67781-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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