University of Illinois Urbana-Champaign

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

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
Date of Ingest
2017-07-27T15:57:48Z
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
Genre of Resource
Conference Poster
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

Owning Collections

iConference 2017 Poster Descriptions PRIMARY