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Hate and False Metaphors: Implications to Emerging E-Participation Environment

Author

Listed:
  • Sreejith Alathur

    (Information Systems, Indian Institute of Management Kozhikode, Kozhikode 673570, India)

  • Naganna Chetty

    (A. J. Institute of Engineering and Technology, Mangaluru 575006, India)

  • Rajesh R. Pai

    (Department of Humanities and Management,Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Vishal Kumar

    (Bipin Tripathi Kumaon Institute of Technology, Dwarahat 263653, India)

  • Sahraoui Dhelim

    (School of Computer Science, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland)

Abstract

This study aims to investigate the effect of metaphorical content on e-participation in healthcare. With this objective, the study assesses the awareness and capability of e-participants to navigate through healthcare metaphors during their participation. Healthcare-related e-participation data were collected from the Twitter platform. Data analysis includes (i) awareness measurements by topic modelling and sentiment analysis and (ii) participation abilities by problem-based learning models. Findings show that a lack of effort to validate metaphors harms e-participation levels and awareness, resulting in a problematic health environment. Exploring metaphors in these intricate forums has the potential to enhance service delivery. Improving web service delivery requires valuable input from stakeholders on the application of metaphors in the health domain.

Suggested Citation

  • Sreejith Alathur & Naganna Chetty & Rajesh R. Pai & Vishal Kumar & Sahraoui Dhelim, 2022. "Hate and False Metaphors: Implications to Emerging E-Participation Environment," Future Internet, MDPI, vol. 14(11), pages 1-10, October.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:11:p:314-:d:959040
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    References listed on IDEAS

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    1. Zhigang Li & Xu Xu, 2020. "Analysis of Network Structure and Doctor Behaviors in E-Health Communities from a Social-Capital Perspective," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    2. Dawei Wei & Feifei Shi & Sahraoui Dhelim, 2022. "A Self-Supervised Learning Model for Unknown Internet Traffic Identification Based on Surge Period," Future Internet, MDPI, vol. 14(10), pages 1-16, October.
    3. Jessica Liu & Caroline Wright & Olga Elizarova & Jennifer Dahne & Jiang Bian & Andy S. L. Tan, 2021. "Emotional Responses and Perceived Relative Harm Mediate the Effect of Exposure to Misinformation about E-Cigarettes on Twitter and Intention to Purchase E-Cigarettes among Adult Smokers," IJERPH, MDPI, vol. 18(23), pages 1-13, November.
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