PuppetChat: Fostering Intimate Communication through Bidirectional Actions and Micronarratives

TL;DR

PuppetChat is a dyadic messaging prototype that restores this expressive depth through embodied interaction and uses a reciprocity aware recommender to encourage responsive actions and generates personalized micronarratives from user stories to ground interactions in personal history.

Abstract

As a primary channel for sustaining modern intimate relationships, instant messaging facilitates frequent connection across distances. However, today's tools often dilute care; they favor single tap reactions and vague emojis that do not support two way action responses, do not preserve the feeling that the exchange keeps going without breaking, and are weakly tied to who we are and what we share. To address this challenge, we present PuppetChat, a dyadic messaging prototype that restores this expressive depth through embodied interaction. PuppetChat uses a reciprocity aware recommender to encourage responsive actions and generates personalized micronarratives from user stories to ground interactions in personal history. Our 10-day field study with 11 dyads of close partners or friends revealed that this approach enhanced social presence, supported more expressive self disclosure, and sustained continuity and shared memories.

Figures (7)

• Figure 1: The main interface of PuppetChat. (A) The contact panel supports user management. (A1) Relationship management through personalized icons. (B) The conversation panel for dyadic exchange. (B1) Personal narrative input for guiding and editing AI generated micronarratives with persona cues. (B2) The interactive puppet area, where puppets animate actions or remain idle in a resting pose (left: partner; right: self). (B3) Action recommendation button that suggests reciprocal actions based on conversational context.
• Figure 2: Workflow of PuppetChat. (A) Everyday chat view. Pressing the Actions button (Fig. \ref{['fig:main_page']} B3) reveals (A1) a recommendation strip with four context aware actions sampled from a 42-item action library (A2), and clicking any action in (A1) advances to (B). (B) Composition view showing (B1) a visual preview of the selected action and an automatically generated micronarrative; tapping (B2) opens the customization panel (C). In (C), users refine tags via (C1) likes and dislikes, (C2) habits, (C3) social interaction style, and (C4) emotion, and may edit (C5) My Story. Clicking "Use Tag to Regenerate" (C6) advances to regenerate the micronarrative based on the selected tags and enables sending.
• Figure 3: Text to action interpretation. (a) Keyword extraction with negation handling aligns user text with action tags; (b) emotional alignment maps input valence (positive, negative, or neutral) to the action's emotion labels; (c) embedding-based fuzzy semantic matching covers indirect or metaphorical expressions.
• Figure 4: Contextual evaluation. (a) Reaction candidate matching: the partner's most recent action queries the action library's ReactionCandidates to prioritize complementary responses; (b) interaction role bias: actions labeled responsive (vs. self oriented) are promoted—conditioned on the ongoing conversational state—to encourage reciprocal exchanges.
• Figure 5: Status views for action delivery and exchange. (a) Action Only: the selected action is dispatched without a micronarrative. (b) Send: the action and the edited micronarrative are delivered together. (c) Partner response: both puppets are co-present and their actions are rendered as an interaction.