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Decomposing the Twitter data stream in healthcare: An information theory perspective
Author(s) -
Zhang Yuan,
Chang HsiaChing
Publication year - 2017
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.2017.14505401184
Subject(s) - dissemination , terminology , variety (cybernetics) , perspective (graphical) , construct (python library) , microblogging , health care , computer science , social media , data science , information dissemination , psychology , world wide web , linguistics , artificial intelligence , political science , telecommunications , philosophy , law , programming language
Recent research using Twitter as an information communication channel has shown how event organizers convey and disseminate their agendas 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 more informative ways to communicate healthcare messages.