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Decomposing and Visualizing the Twitter Data Stream with Healthcare Hashtags: An Information Theoretical Perspective

In: Knowledge Discovery and Data Design Innovation Proceedings of the International Conference on Knowledge Management (ICKM 2017)

Author

Listed:
  • Yuan Zhang
  • Hsia-Ching Carrie Chang

Abstract

Recent research using Twitter as an information communication channel has shown how event organizers convey and disseminate their agenda across industries and disciplines. However, little research has been carried out on the user’s choice of information components when composing a tweet through the lens of information theory. This research employs a comparative case study to examine how medical-terminology hashtags and corresponding lay-language hashtags have been used to help to communicate healthcare messages on the Twitter platform. The main result of this case study revealed patterns that both retweeting behavior and the use of a variety of components to construct a tweet contribute to higher entropy values which imply that these are a more informative ways to communicate healthcare messages.

Suggested Citation

  • Yuan Zhang & Hsia-Ching Carrie Chang, 2017. "Decomposing and Visualizing the Twitter Data Stream with Healthcare Hashtags: An Information Theoretical Perspective," World Scientific Book Chapters, in: Daniel Gelaw Alemneh & Jeff Allen & Suliman Hawamdeh (ed.), Knowledge Discovery and Data Design Innovation Proceedings of the International Conference on Knowledge Management (ICKM 2017), chapter 3, pages 47-66, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789813234482_0003
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    More about this item

    Keywords

    Knowledge Discovery; Big Data; Data Science; Data Analytics; Innovation;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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