Your browser doesn't support javascript.
loading
Illusory interparty disagreement: Partisans agree on what hate speech to censor but do not know it.
Solomon, Brittany C; Hall, Matthew E K; Hemmen, Abigail; Druckman, James N.
Afiliação
  • Solomon BC; Department of Management and Organization, University of Notre Dame, Notre Dame, IN.
  • Hall MEK; Department of Political Science, University of Notre Dame, Notre Dame, IN.
  • Hemmen A; Department of Political Science, University of Notre Dame, Notre Dame, IN.
  • Druckman JN; Department of Political Science, University of Rochester, Rochester, NY.
Proc Natl Acad Sci U S A ; 121(39): e2402428121, 2024 Sep 24.
Article em En | MEDLINE | ID: mdl-39284056
ABSTRACT
Whether and when to censor hate speech are long-standing points of contention in the US. The latest iteration of these debates entails grappling with content regulation on social media in an age of intense partisan polarization. But do partisans disagree about what types of hate speech to censor on social media or do they merely differ on how much hate speech to censor? And do they understand out-party censorship preferences? We examine these questions in a nationally representative conjoint survey experiment (participant N = 3,357; decision N = 40,284). We find that, although Democrats support more censorship than Republicans, partisans generally agree on what types of hate speech are most deserving of censorship in terms of the speech's target, source, and severity. Despite this substantial cross-party agreement, partisans mistakenly believe that members of the other party prioritize protecting different targets of hate speech. For example, a major disconnect between the two parties is that Democrats overestimate and Republicans underestimate the other party's willingness to censor speech targeting Whites. We conclude that partisan differences on censoring hate speech are largely based on free speech values and misperceptions rather than identity-based social divisions.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Política Limite: Female / Humans / Male País/Região como assunto: America do norte Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Política Limite: Female / Humans / Male País/Região como assunto: America do norte Idioma: En Ano de publicação: 2024 Tipo de documento: Article