IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v43y2024i3p507-522.html
   My bibliography  Save this article

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

Author

Listed:
  • Long Ma
  • Lu Zheng

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.

Suggested Citation

  • Long Ma & Lu Zheng, 2024. "Ego-networks, SNSs affordances, and personalities: understanding individuals’ selfie posting on SNSs based on Actor-Network Theory," Behaviour and Information Technology, Taylor & Francis Journals, vol. 43(3), pages 507-522, February.
  • Handle: RePEc:taf:tbitxx:v:43:y:2024:i:3:p:507-522
    DOI: 10.1080/0144929X.2023.2177824
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2023.2177824
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0144929X.2023.2177824?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tbitxx:v:43:y:2024:i:3:p:507-522. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.