Zhang, YuanChang, Hsia-Ching2017-12-282017-12-282018-01-03978-0-9981331-1-9http://hdl.handle.net/10125/50294Little research in information system has been carried out on the subject of user’s choice of different components when composing a tweet through the analytical lens of information theory. This study employs a comparative case study approach to examine the use of hashtags of medical-terminology versus lay-language in tweet-trails and (1) introduces a novel H(x) index to reveal the complexity in the statistical structure and the variety in the composition of a tweet-trail, (2) applies radar graph and scatter plot as intuitive data visualization aids, and (3) proposes a methodological framework for structural analysis of Twitter data stream as a supplemental tool for profile analysis of Twitter users and content analysis of tweets. This systematic framework is capable of unveiling patterns in the structure of tweet-trails and providing quick and preliminary snap shots (selfies) of Twitter data stream because it’s an automatic and objective approach which requires no human intervention.10 pagesengAttribution-NonCommercial-NoDerivatives 4.0 InternationalPersonal Health Management and Technologiesdata visualization, entropy, information theory, structural analysis, TwitterConference Paper10.24251/HICSS.2018.406