Present, endorsed, and active: Instagram cues that predict trust

Abstract

This study examines variables of Instagram profiles that predict trust of online collaborators. We employed supervised machine learning with logistic regression to identify factors of Instagram profiles that predict trustworthiness of a potential rideshare partner. Exploratory factor analysis was used to identify latent factors of Instagram profiles that influence judgments of trust. Informed by the MAIN model, results identified three variables of Instagram profiles that predicted trust judgments: personal presence, bandwagon cues, and public activity. We discuss the implications of these findings in relation to theory on heuristics and credibility, the role of trust in collaborative technologies, and the communication of trust through social media.

Keywords:

• Credibility
• Heuristics
• Main Model
• Social Media
• Trust

Disclosure statement

No competing financial interests exist for any of the authors.