Same Stories, Different Journeys: From Social Comparison to Sensemaking in AI-Mediated Peer Career Exploration

2026-07-12

AI Summary

This study addresses how young job seekers, when passively browsing peers’ career-related content on social media, are prone to detrimental upward social comparisons and cognitive overload, which impede effective career exploration. To mitigate these issues, this work proposes JobMate—a novel system that integrates authentic user-generated career posts with conversational AI. By constructing persona-based, interactive AI agents, JobMate shifts users from passive consumption toward active, personalized dialogue-driven exploration. The approach preserves the emotional authenticity of real peer narratives while transforming social comparison into a constructive process of self-reconstruction and meaning-making. A user study (N=24) demonstrates that JobMate significantly reduces harmful comparisons, fosters proactive dialogue and sensemaking, and leverages genuine peer content to provide emotional support.

Abstract

Young job seekers frequently turn to social media to compare themselves with peers and make sense of career possibilities. However, passive feed browsing creates a paradox: the authentic peer content that provides emotional grounding also triggers potentially detrimental upward social comparison and cognitive overload. Previous work has either structured online user-generated content to reduce noise without changing the passive browsing modality, or built AI-powered career exploration systems that disregard authentic human experiences. To address this gap, we developed JobMate, an interactive system that transforms real social media career posts into persona-grounded conversational AI agents, shifting the interaction from passive scrolling to active, personalized dialogue. We conducted a between-subjects study ($N$ = 24, three disciplines) comparing JobMate with native RedNote browsing. Our study shows that JobMate's AI-mediated dialogue redirected social comparison from potentially detrimental upward comparison toward constructive self-reframing, while promoting sensemaking through active conversational engagement. However, users still relied on the authenticity of real peer content for emotional grounding. We discuss design implications for AI systems that augment authentic online user-generated content consumption across social comparison contexts.

Problem

• social comparison
• career exploration
• AI-mediated interaction
• sensemaking
• user-generated content

Innovation

• AI-mediated dialogue
• persona-grounded agents
• social comparison
• career exploration
• sensemaking