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

Yuan Zhang and Hsia-Ching Carrie Chang

Chapter 3 in Knowledge Discovery and Data Design Innovation:Proceedings of the International Conference on Knowledge Management (ICKM 2017), 2017, pp 47-66 from World Scientific Publishing Co. Pte. Ltd.

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.

Keywords: Knowledge Discovery; Big Data; Data Science; Data Analytics; Innovation (search for similar items in EconPapers)
JEL-codes: O30 (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.worldscientific.com/doi/pdf/10.1142/9789813234482_0003 (application/pdf)
https://www.worldscientific.com/doi/abs/10.1142/9789813234482_0003 (text/html)
Ebook Access is available upon purchase.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:wschap:9789813234482_0003

Ordering information: This item can be ordered from

Access Statistics for this chapter

More chapters in World Scientific Book Chapters from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().