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Assessment of Social Interaction Behaviors
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Talking Less during Social Interactions Predicts Enjoyment: A Mobile Sensing Pilot Study.

Gillian M Sandstrom1, Vincent Wen-Sheng Tseng2, Jean Costa2

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Enjoyable conversations can be predicted by non-verbal cues. People enjoyed conversations more when they spoke less, highlighting the role of conversational properties in social well-being.

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Area of Science:

  • Psychology
  • Human-Computer Interaction
  • Sociology

Background:

  • Assessing the quality of everyday social interactions is crucial for understanding well-being.
  • Traditional methods for studying conversations are often limited to self-reports or laboratory settings.
  • Mobile technology offers new possibilities for unobtrusively collecting data on real-world social experiences.

Purpose of the Study:

  • To investigate whether non-verbal conversational properties can predict conversation enjoyment.
  • To explore the utility of mobile sensing in capturing everyday social interactions.
  • To determine if acoustical and conversational features correlate with subjective enjoyment.

Main Methods:

  • 36 participants used the 'My Social Ties' mobile app to record data from 473 daily conversations.
  • Analyzed conversational properties: length, turn-taking rate, and proportion of speaking time.
  • Examined acoustical properties: volume and pitch.

Main Results:

  • Conversation enjoyment was surprisingly higher when participants spoke a smaller proportion of the time.
  • Conversational properties, not just acoustical ones, significantly predicted enjoyment.
  • The study demonstrated a link between objective interaction patterns and subjective experience.

Conclusions:

  • Non-verbal conversational dynamics are key predictors of conversation enjoyment.
  • Mobile sensing provides valuable insights into everyday social interactions and psychological well-being.
  • This pilot study supports the potential of technology to enhance our understanding of social connection.