Logarithmic versus Linear Visualizations of Covid-19 Cases Do Not Affect Citizens’ Support for Confinement
Bibliographic Data
| ID | 6236745 |
|---|---|
| Authors | Semra Sevi (0000-0001-7886-4616, Université de Montréal, corresponding author), Marco Mendoza Aviña (0000-0001-8102-938X, Université de Montréal), Gabrielle Péloquin-Skulski (0000-0003-1504-0286, Université de Montréal), Emmanuel Heisbourg (0000-0002-9192-0114, Université de Montréal), Paola Vegas (Université de Montréal), Maxime Coulombe (0000-0001-5449-4577, Université de Montréal), Vincent Arel-Bundock (0000-0003-2042-7063, Université de Montréal), Peter John Loewen (0000-0003-2690-4158, University of Toronto), André Blais (0000-0003-4292-110X, Université de Montréal) |
| Year | 2020 |
| Volume | 53 |
| Issue | 2 |
| Pages | 385-390 |
| Publication date | 2020-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Canadian Journal of Political Science (JOURNAL) |
| Journal identifiers | ISSN: 0008-4239 • E-ISSN: 1744-9324 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s000842392000030x |
| OpenAlex | W3015204092 |
| Language | EN |
| Citations received | 14 |
| References cited | 5 |
The SARS-CoV-2 virus was first identified in Wuhan, China, in late December 2019, and it quickly spread to many countries. By March 2020, the virus had triggered a global pandemic (World Health Organization, 2020). In response to this crisis, governments have implemented unprecedented public health measures. The success of these policies will largely depend on the public's willingness to comply with new rules. A key factor in citizens’ willingness to comply is their understanding of the data that motivate government action. In this study, we examine how different ways of presenting these data visually can affect citizen's perceptions, attitudes and support for public policy
Action (physics · Affect (linguistics · Business · China · Coronavirus disease 2019 (COVID-19 · Disease · Government (linguistics · Pandemic · Perception · Political science · Public health · Public relations · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Crime Patterns and Interventions · Electoral Systems and Political Participation · Medicine · Nursing · Psychology · Social Media and Politics
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| Unique citing works | 14 |
|---|---|
| Citations per year | 2,33 |
| Citation span | 2020 - 2025 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 14 |