Exploring the effects of social capital on the compulsive use of online social networks in civil unrest contexts.

Bonding social capital Bridging social capital Compulsive usage behaviour Partial least squares structural equation modelling (PLS-SEM) Social capital theory Social networking sites (SNS)

Journal

Heliyon
ISSN: 2405-8440
Titre abrégé: Heliyon
Pays: England
ID NLM: 101672560

Informations de publication

Date de publication:
Jul 2022
Historique:
received: 24 09 2021
revised: 31 03 2022
accepted: 13 07 2022
pubmed: 26 7 2022
medline: 26 7 2022
entrez: 25 7 2022
Statut: epublish

Résumé

The use of online social networking sites has become part of everyday life for more than three billion people worldwide. However, its use may go beyond being a habit, leading to compulsive use behaviours that jeopardize the well-being of an individual and the whole society. This study proposes and evaluates a theoretical model that examines the four dimensions of social capital, mediated by bonding and bridging social capital, as drivers of compulsive use of online social networks in the context of civil unrest. We evaluate the model using partial least squares structural equation modelling with data collected from a developing country. We found that reciprocity is the most important driver for bonding and bridging social capital with online members. Whereas trust, contradicting most of the literature in the field, was not statistically significant over bonding and bridging social capital. Bonding social capital shows a significant association with compulsive use behaviour. On the other hand, the effect of bridging social capital on compulsive use behaviour, although not significant, may become significant in the presence of a strong usage habit.

Identifiants

pubmed: 35874073
doi: 10.1016/j.heliyon.2022.e09990
pii: S2405-8440(22)01278-6
pmc: PMC9305364
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e09990

Informations de copyright

© 2022 The Author(s).

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Auteurs

Mijail Naranjo-Zolotov (M)

NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisbon, Portugal.

Albert Acedo (A)

NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisbon, Portugal.
GEOTEC, Institute of New Imaging Technologies, Universitat Jaume I, Castelló de la Plana, Spain.
ITI/LARSyS, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.

Jorge Edison Lascano (JE)

Department of Computer Sciences, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador.

Classifications MeSH