How People React to Zika Virus Outbreaks on Twitter? A Computational Content Analysis

King Wa Fu; Hai Liang; Nitin Saroha; Zion Tsz Ho Tse; Patrick Ip; Isaac Chun Hai Fung

doi:10.1016/j.ajic.2016.04.253

How People React to Zika Virus Outbreaks on Twitter? A Computational Content Analysis

King Wa Fu, Hai Liang, Nitin Saroha, Zion Tsz Ho Tse, Patrick Ip, Isaac Chun Hai Fung

Biostatistics, Epidemiology & Environmental Health Sciences

Research output: Contribution to journal › Article › peer-review

109 Scopus citations

Abstract

Zika-related Twitter incidence peaked after the World Health Organization declared an emergency. Five themes were identified from Zika-related Twitter content: (1) societal impact of the outbreak; (2) government, public and private sector, and general public responses to the outbreak; (3) pregnancy and microcephaly: negative health consequences related to pregnant women and babies; (4) transmission routes; and (5) case reports. User-generated contents sites were preferred direct information channels rather than those of the government authorities.

Original language	American English
Journal	American Journal of Infection Control
Volume	44
DOIs	https://doi.org/10.1016/j.ajic.2016.04.253
State	Published - Dec 1 2016

Disciplines

Public Health
Biostatistics
Environmental Public Health
Epidemiology

Keywords

Health communication
Pregnancy Complications
Public Response
Social Media
Zika Virus Disease

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.ajic.2016.04.253License: Unspecified

https://doi.org/10.1016/j.ajic.2016.04.253

Cite this

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title = "How People React to Zika Virus Outbreaks on Twitter? A Computational Content Analysis",

abstract = "Zika-related Twitter incidence peaked after the World Health Organization declared an emergency. Five themes were identified from Zika-related Twitter content: (1) societal impact of the outbreak; (2) government, public and private sector, and general public responses to the outbreak; (3) pregnancy and microcephaly: negative health consequences related to pregnant women and babies; (4) transmission routes; and (5) case reports. User-generated contents sites were preferred direct information channels rather than those of the government authorities.",

keywords = "Health communication, Pregnancy Complications, Public Response, Social Media, Zika Virus Disease",

author = "Fu, {King Wa} and Hai Liang and Nitin Saroha and Tse, {Zion Tsz Ho} and Patrick Ip and Fung, {Isaac Chun Hai}",

note = "Publisher Copyright: {\textcopyright} 2016 Association for Professionals in Infection Control and Epidemiology, Inc.",

year = "2016",

month = dec,

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doi = "10.1016/j.ajic.2016.04.253",

language = "American English",

volume = "44",

journal = "American Journal of Infection Control",

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T1 - How People React to Zika Virus Outbreaks on Twitter? A Computational Content Analysis

AU - Fu, King Wa

AU - Liang, Hai

AU - Saroha, Nitin

AU - Tse, Zion Tsz Ho

AU - Ip, Patrick

AU - Fung, Isaac Chun Hai

PY - 2016/12/1

Y1 - 2016/12/1

N2 - Zika-related Twitter incidence peaked after the World Health Organization declared an emergency. Five themes were identified from Zika-related Twitter content: (1) societal impact of the outbreak; (2) government, public and private sector, and general public responses to the outbreak; (3) pregnancy and microcephaly: negative health consequences related to pregnant women and babies; (4) transmission routes; and (5) case reports. User-generated contents sites were preferred direct information channels rather than those of the government authorities.

AB - Zika-related Twitter incidence peaked after the World Health Organization declared an emergency. Five themes were identified from Zika-related Twitter content: (1) societal impact of the outbreak; (2) government, public and private sector, and general public responses to the outbreak; (3) pregnancy and microcephaly: negative health consequences related to pregnant women and babies; (4) transmission routes; and (5) case reports. User-generated contents sites were preferred direct information channels rather than those of the government authorities.

KW - Health communication

KW - Pregnancy Complications

KW - Public Response

KW - Social Media

KW - Zika Virus Disease

UR - https://digitalcommons.georgiasouthern.edu/bee-facpubs/12

UR - https://doi.org/10.1016/j.ajic.2016.04.253

U2 - 10.1016/j.ajic.2016.04.253

DO - 10.1016/j.ajic.2016.04.253

M3 - Article

SN - 0196-6553

VL - 44

JO - American Journal of Infection Control

JF - American Journal of Infection Control

ER -

How People React to Zika Virus Outbreaks on Twitter? A Computational Content Analysis

Abstract

Disciplines

Keywords

UN SDGs

Access to Document

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