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Self-Disclosure Characteristics and Motivations in Social Media

Extending the Functional Model to Multiple Social Network Sites

Datos Bibliográficos

ID2264216
AutoresYoon Hyung Choi (0000-0003-2561-4554, Department of Communication; Cornell University; Ithaca NY 14853-4203 USA), Natalie N Bazarova (0000-0001-5375-6598, Cornell University), Natalya N Bazarova (Department of Communication; Cornell University; Ithaca NY 14853-4203 USA)
Año2015
Volumen41
Número4
Páginas480-500
Fecha de publicación2015-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaHuman Communication Research (JOURNAL)
Identificadores de la revistaISSN: 0360-3989 • E-ISSN: 1468-2958
EditorialOxford University Press (OUP) (PUBLISHER)
DOI10.1111/hcre.12053
OpenAlexW1516009960
IdiomaEN
Citas recibidas36
Referencias citadas29

The purpose of this study was to examine differences in self-disclosure goals, privacy concerns, and self-disclosure characteristics between Facebook and Twitter. These sites were compared in terms of audience representations, based on structural cues that suggest potential audiences for a user. We conceptualized audience representations in 2 ways: based on privacy boundaries that imply bounded versus unbounded audiences, and on network characteristics such as size and diversity for audiences within the boundary. Results revealed that self-disclosure goals, privacy concerns, and self-disclosure intimacy were different depending on the privacy boundary. Network characteristics were also important, but effects were moderated by the privacy boundary type, suggesting a complex interplay between the 2 types of audience representations in shaping self-disclosure in social media

Boundary (topology · Diversity (politics · Internet privacy · Self-disclosure · Social media · Social network (sociolinguistics · Sociology · World Wide Web · Computer Science · Impact of Technology on Adolescents · Privacy, Security, and Data Protection · Psychology · Social Media and Politics · Social Psychology

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Obras citantes distintas36
Citas por año3,6
Intervalo de citas2016 - 2026 (11)
Velocidad de citacióncurrent
Altamente citadoNo
Tipos de citaNeutras: 35
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