Decomposing the Twitter data stream in healthcare: An information theory perspective

被引：0

作者：

Zhang Y. ^{[1
]}

Chang H.-C. ^{[1
]}

机构：

[1] University of North Texas, United States

来源：

Proceedings of the Association for Information Science and Technology | 2017年 / 54卷 / 01期

关键词：

hashtag; healthcare; information theory; tweets; Twitter;

D O I：

10.1002/pra2.2017.14505401184

中图分类号：

学科分类号：

摘要：

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. Copyright © 2017 by Association for Information Science and Technology

引用

页码：853 / 854

页数：1

共 7 条

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