Ego-networks, SNSs affordances, and personalities: understanding individuals’ selfie posting on SNSs based on Actor-Network Theory

Long Ma and Lu Zheng

Behaviour and Information Technology, 2024, vol. 43, issue 3, 507-522

Abstract: The prevalence of smartphones and social networking sites (SNSs) has given rise to the popularity of selfie posting, presenting one’s own photograph on SNSs. While previous studies have mainly investigated the effects of personal characteristics (e.g. demographics, personality traits and motivational needs) on selfie posting, the impacts exerted by individuals’ social networks have been largely neglected. Drawing on the Actor-Network Theory, this study explores besides personal traits (i.e. personalities and demographics), how relational characteristics of one’s ego networks (i.e. gender heterogeneity, age homophily, average tie strength, and network density) and SNSs affordances (i.e. connectivity and interactivity) affect selfie posting behavior. Based on a survey sample in which the respondents’ ego network data were collected, individuals’ ego-network metrics were calculated and analyzed. Our analyses show that those whose ego network having a higher proportion of opposite sex (measured by gender heterogeneity) or/and having alters more connected with one another (measured by network density) are more likely to post selfie on SNSs, while those embedded in a strong-tie network (measured by average tie strength) are less likely to post selfie on SNSs. The findings suggest that characteristics of one’s ego network exert important influences on selfie posting on SNSs.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2023.2177824 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:43:y:2024:i:3:p:507-522

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2023.2177824

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().