Literature DB >> 30408201

Rethinking Social Amplification of Risk: Social Media and Zika in Three Languages.

Christopher D Wirz1, Michael A Xenos1, Dominique Brossard1,2, Dietram Scheufele1,2, Jennifer H Chung1, Luisa Massarani3.   

Abstract

Using the Zika outbreak as a context of inquiry, this study examines how assigning blame on social media relates to the social amplification of risk framework (SARF). Past research has discussed the relationship between the SARF and traditional mass media, but the role of social media platforms in amplification or attenuation of risk perceptions remains understudied. Moreover, the communication and perceptions of Zika-related risk are not limited to discussions in English. To capture conversations in languages spoken by affected countries, this study combines data in English, Spanish, and Portuguese. To better understand the assignment of blame and perceptions of risk in new media environments, we looked at three different facets of conversations surrounding Zika on Facebook and Twitter: the prominence of blame in each language, how specific groups were discussed throughout the Zika outbreak, and the sentiment expressed about genetically engineered (GE) mosquitoes. We combined machine learning with human coding to analyze public discourse in all three languages. We found differences between languages and platforms in the amount of blame assigned to different groups. We also found more negative sentiments expressed about GE mosquitoes on Facebook than on Twitter. These meaningful differences only emerge from analyses across the three different languages and platforms, pointing to the importance of multilingual approaches for risk communication research. Specific recommendations for outbreak and risk communication practitioners are also discussed.
© 2018 Society for Risk Analysis.

Entities:  

Keywords:  Blame; GE mosquitoes; SARF

Mesh:

Year:  2018        PMID: 30408201     DOI: 10.1111/risa.13228

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  9 in total

1.  Social Risk Perceptions of Genetically Modified Foods of Engineers in Training: Application of a Comprehensive Risk Model.

Authors:  Sedigheh Ghasemi; Mostafa Ahmadvand; Ezatollah Karami; Ayatollah Karami
Journal:  Sci Eng Ethics       Date:  2019-05-23       Impact factor: 3.525

2.  Public perceptions of threats from mosquitoes in the U.S. using online media analytics.

Authors:  Nicole J Olynk Widmar; Courtney Bir; Evan Long; Audrey Ruple
Journal:  Pathog Glob Health       Date:  2020-11-08       Impact factor: 2.894

3.  Relationship between the actual fine dust concentration and media exposure that influenced the changes in outdoor activity behavior in South Korea.

Authors:  Myung-Gwan Kim; Su-Jin Lee; Donghwi Park; Chul-Hyun Kim; Ki- Hoon Lee; Jong-Moon Hwang
Journal:  Sci Rep       Date:  2020-07-20       Impact factor: 4.379

4.  An Empirical Study on the Influence Path of Environmental Risk Perception on Behavioral Responses In China.

Authors:  Shan Gao; Weimin Li; Shuang Ling; Xin Dou; Xiaozhou Liu
Journal:  Int J Environ Res Public Health       Date:  2019-08-10       Impact factor: 3.390

5.  [Risk perception and information behaviour of opinion leaders in the food sector].

Authors:  Ann-Kathrin Lindemann; Katrin Jungnickel; Gaby-Fleur Böl
Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz       Date:  2020-12-08       Impact factor: 1.513

6.  Risk sharing on Twitter: Social amplification and attenuation of risk in the early stages of the COVID-19 pandemic.

Authors:  Xiaochen Angela Zhang; Raluca Cozma
Journal:  Comput Human Behav       Date:  2021-08-14

Review 7.  Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review.

Authors:  Agam Bansal; Rana Prathap Padappayil; Chandan Garg; Anjali Singal; Mohak Gupta; Allan Klein
Journal:  J Med Syst       Date:  2020-08-01       Impact factor: 4.460

8.  The Evolving Field of Risk Communication.

Authors:  Dominic Balog-Way; Katherine McComas; John Besley
Journal:  Risk Anal       Date:  2020-10-20       Impact factor: 4.000

9.  Identification of affective valence of Twitter generated sentiments during the COVID-19 outbreak.

Authors:  Ruchi Mittal; Amit Mittal; Ishan Aggarwal
Journal:  Soc Netw Anal Min       Date:  2021-10-27
  9 in total

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