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

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.