Uncovering hidden behavioral patterns in the era of “we media”: Modeling spatio-temporal dynamics for twitter news

Huang, Hong; Yu, Han; Andrews, James E.; Yoon, JungWon; Burgess, Kelsey L.

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https://hdl.handle.net/2142/96703 Copy

Description

Title

Uncovering hidden behavioral patterns in the era of “we media”: Modeling spatio-temporal dynamics for twitter news

Author(s)

• Huang, Hong
• Yu, Han
• Andrews, James E.
• Yoon, JungWon
• Burgess, Kelsey L.

Issue Date

2017

Keyword(s)

• Twitter news
• Genetic test
• Gene patent
• Twitter geolocations
• Twitter timestamp

Abstract

This research presents a Bayesian statistical model to examine spatio-temporal effects for Twitter use when reporting important events or news. The proposed model tests the Twitter News data surrounding the United States Supreme Court’s Myriad Genetics, Inc. June 13, 2013 decision and its impact on direct-to-consumer genetic testing and gene patenting. The model demonstrates the sensitivity in distinguishing the behaviours of Twitter users’ followers with and without adjusting spatio-temporal effects. It was also found that media professionals’ tweets were coming thick and quick, and producing “waves” of engagement of followers. However, grassroots actively participate in tweeting and constantly engage more followers. The model maps tweets across the spatial heterogeneity and temporal evolution in the early and post recognition and discussion of events. These findings demonstrate the importance of spatio-temporal effects to influence professionals or non-professionals for tweeting. The model also guided researchers to detect sub-events with low latency.

Publisher

iSchools

Series/Report Name or Number

iConference 2017 Proceedings

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/96703

Copyright and License Information

Copyright 2017 Hong Huang, Han Yu, James E. Andrews, JungWon Yoon, and Kelsey L. Burgess

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