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Data Management and AnalysisBig Data Analytics of Twitter Data and Its Application for Physician Assistants: Who Is Talking About Your Profession in Twitter?

Data Management and Analysis: Big Data Analytics of Twitter Data and Its Application for... [In the current era of big data, huge volumes of a wide variety of valuable data—which may be of different veracity—are easily generated or collected at a high velocity in various real-life applications. A rich source of complex big data is social networking sites (e.g., Twitter, Facebook, LinkedIn), in which many people are connected with each other. For many of these creators of social network data (i.e., users on the social networking sites), it is not unusual for them to have hundreds or even thousands of friends or connections. Among these friends or connections, some of them care about you as an individual user or friend, while some others care or talk about your profession. It is interesting to know how many of your friends or connections know about your profession, understand it, and talk about it. This chapter presents a system for big data analytics of Twitter data. In particular, we design a system to allow non-computer experts to extract interesting information from the social network (especially, Twitter) data. To demonstrate the practicality of the system, we also conduct a case study to demonstrate how the system helps physician assistants (PAs) to find interesting pattern from tweets about their profession.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Data Management and AnalysisBig Data Analytics of Twitter Data and Its Application for Physician Assistants: Who Is Talking About Your Profession in Twitter?

Part of the Studies in Big Data Book Series (volume 65)
Editors: Alhajj, Reda; Moshirpour, Mohammad; Far, Behrouz
Data Management and Analysis — Dec 21, 2019

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References (9)

Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2020
ISBN
978-3-030-32586-2
Pages
17 –32
DOI
10.1007/978-3-030-32587-9_2
Publisher site
See Chapter on Publisher Site

Abstract

[In the current era of big data, huge volumes of a wide variety of valuable data—which may be of different veracity—are easily generated or collected at a high velocity in various real-life applications. A rich source of complex big data is social networking sites (e.g., Twitter, Facebook, LinkedIn), in which many people are connected with each other. For many of these creators of social network data (i.e., users on the social networking sites), it is not unusual for them to have hundreds or even thousands of friends or connections. Among these friends or connections, some of them care about you as an individual user or friend, while some others care or talk about your profession. It is interesting to know how many of your friends or connections know about your profession, understand it, and talk about it. This chapter presents a system for big data analytics of Twitter data. In particular, we design a system to allow non-computer experts to extract interesting information from the social network (especially, Twitter) data. To demonstrate the practicality of the system, we also conduct a case study to demonstrate how the system helps physician assistants (PAs) to find interesting pattern from tweets about their profession.]

Published: Dec 21, 2019

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