Understanding Technological Features and Emotional Contagion

PROJECT SUMMARY

How do different communication tools shape emotional connection during supportive conversations? In this research project, I examined whether features of communication channels—such as video, voice, or text—affect emotional contagion and the perceived quality of supportive interactions.

Role: Principal Investigator

Methods: Remote lab experiments, surveys, structural equation modeling

Context: Interpersonal communication, emotional support, digital interaction

THEORETICAL FOUNDATION

This work builds on three key theories of communication and emotion:

• Media Richness Theory suggests that richer media (e.g., video) are more effective at conveying emotional nuance due to immediate feedback and multiple cues.

• Social Presence Theory argues that a greater sense of presence in a medium strengthens interpersonal and emotional engagement.

• Emotion as Social Information (EASI) Theory proposes that emotional expressions influence others through two pathways:

  • • Inferential processes, where people use emotions as information to interpret situations.

    • Affective reactions, where people emotionally respond to others’ expressions, shaping their own behavior.

Together, these theories predict stronger emotional transmission in richer communication channels—an assumption this research set out to test.

RESEARCH QUESTIONS

• How does emotional contagion vary across communication channels (video, voice, text)?

• How does the depth of a support seeker’s disclosure influence emotional contagion?

• How does emotional contagion shape both partners’ evaluations of the interaction?

RESEARCH PROCESS

Study Design

• Participants were recruited in established relationship dyads.

• Each pair joined a remote research session together.

• One participant was assigned the role of support seeker, sharing a recent stressful experience.

• The other participant acted as a support provider.

Procedure

• Participants completed a pre-interaction survey.

• Dyads were randomly assigned to one communication channel:

  • • Video call

    • Voice call

    • Text-based chat

• Partners engaged in a 15-minute supportive conversation.

• Both participants completed a post-interaction survey assessing emotional experience and interaction quality.

ANALYSIS & KEY FINDINGS

Analysis: Multi-group structural equation modeling

*Some R syntax associated with project can be found at https://github.com/vu-nhung/Emotional-Contagion-via-Tech 

Key insights: 

• Emotional contagion did not significantly differ across communication channels. Emotional transmission occurred at similar levels in video, voice, and text-based interactions.

• Greater self-disclosure led to stronger emotional contagion, regardless of channel. When support seekers shared more about their experience, emotions were more strongly transmitted between partners.

• Emotional contagion predicted better interaction outcomes. The more emotional contagion support providers experienced, the more positively both partners evaluated the interaction.

• Support receivers benefited more from audio only channel, whereas support providers benefited more from video calls. 

DESIGN TAKEAWAYS

When emotional cues are limited, people adapt.

In text-based interactions—where facial expressions and tone of voice are absent—participants strategically used available tools such as emojis and expressive language to convey emotion. Rather than reducing emotional connection, lean media encouraged creative emotional expression.

Implications for UX Design

• Emotional connection does not require high-bandwidth features like video or voice.

• Well-designed text-based interfaces can effectively support emotional resonance.

• Designers of messaging platforms, online support tools, and social systems should focus on:

  • • Flexible expressive tools (e.g., emojis, reactions, formatting)

    • Supporting meaningful self-disclosure

    • Reducing friction in emotionally sensitive interactions