Paper Number
ICIS2026-3290
Paper Type
Completed
Abstract
AI technologies are changing digital professional environments facilitating the large-scale production of realistic but potentially misleading content. This study explores signaling dynamics on LinkedIn, examining how professional identity, credibility, and trust are constructed and evaluated in the context of AI-driven content. Based on 25 semi-structured expert interviews analyzed through the Gioia methodology, we identify key elements shaping these dynamics: (1) platform use and signaling, (2) trust and credibility construction, (3) AI and information integrity challenges, (4) verification and adaptive user responses, (5) user typologies. Findings reveal a tension between costly and low-cost signals due to AI-generated content, resulting in increased ambiguity and reduced transparency in professional evaluations. Users and platforms develop strategies such as verification practices and transparency-enhancing features to navigate these challenges. This study developed a framework for signaling dynamics on professional social media, offering insights for creating more trustworthy digital platforms and improving online identity signaling in the age of AI.
Recommended Citation
Azad, Nasreen, "Content Credibility Signaling and Trust in Professional Social Networks: Evidence from LinkedIn" (2026). ICIS 2026 Proceedings. 15.
https://aisel.aisnet.org/icis2026/social/social/15
Content Credibility Signaling and Trust in Professional Social Networks: Evidence from LinkedIn
AI technologies are changing digital professional environments facilitating the large-scale production of realistic but potentially misleading content. This study explores signaling dynamics on LinkedIn, examining how professional identity, credibility, and trust are constructed and evaluated in the context of AI-driven content. Based on 25 semi-structured expert interviews analyzed through the Gioia methodology, we identify key elements shaping these dynamics: (1) platform use and signaling, (2) trust and credibility construction, (3) AI and information integrity challenges, (4) verification and adaptive user responses, (5) user typologies. Findings reveal a tension between costly and low-cost signals due to AI-generated content, resulting in increased ambiguity and reduced transparency in professional evaluations. Users and platforms develop strategies such as verification practices and transparency-enhancing features to navigate these challenges. This study developed a framework for signaling dynamics on professional social media, offering insights for creating more trustworthy digital platforms and improving online identity signaling in the age of AI.
Comments
24_Social_media