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Analysis of Malaria Information on a Social Media Platform

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Design, Operation and Evaluation of Mobile Communications (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12796))

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Abstract

This study explores malaria-related YouTube posts in Africa to identify patterns, themes and terms related to malaria.

Mixed method research was used where both qualitative and quantitative research paradigms were employed. Subject analysis method and Multidimensional scaling (MDS) technique were adapted in this study to discover themes and visualize related terms. Visual analyses were conducted at two levels: subject analysis within categories and category analysis among the categories in a malaria related schema. There were four resultant categories (Causes and facilitators of malaria pandemic, Methods of prevention and treatment of malaria, Effects of malaria, and Vulnerable population) from the subject analysis. The subject hierarchy and subcategories of the schema are associated with a group of relevant terms related to malaria in Africa.

The findings of this research study shed light on understanding malaria related information from the social media perspective, help users seek more relevant information on malaria, enrich existing thesaurus or subject headings by adding new terms related to malaria, and create a more user-oriented subject directory for malaria related portals or websites.

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Authors and Affiliations

  1. School of Information Studies, University of Wisconsin, Milwaukee, WI, 53201, USA

    Benjamin Omwando & Jin Zhang

Authors
  1. Benjamin Omwando
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  2. Jin Zhang
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Correspondence to Benjamin Omwando .

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Editors and Affiliations

  1. University of Central Florida, Orlando, FL, USA

    Gavriel Salvendy

  2. College of Business, University of West Florida, Pensacola, FL, USA

    June Wei

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Omwando, B., Zhang, J. (2021). Analysis of Malaria Information on a Social Media Platform. In: Salvendy, G., Wei, J. (eds) Design, Operation and Evaluation of Mobile Communications. HCII 2021. Lecture Notes in Computer Science(), vol 12796. Springer, Cham. https://doi.org/10.1007/978-3-030-77025-9_25

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  • DOI: https://doi.org/10.1007/978-3-030-77025-9_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77024-2

  • Online ISBN: 978-3-030-77025-9

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