# Affective and Conversational Predictors of Re-Engagement in Human-Robot Interactions -- A Student-Centered Study with A Humanoid Social Robot

arXiv: https://arxiv.org/abs/2503.16449 · HTML: https://mlsanity.com/paper/2503.16449/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 65 references that are in the map.
- First posted on arXiv 18 Feb 2025.

## Builds on (most cited first, 10 of 10)

- [Duplex Conversation: Towards Human-like Interaction in Spoken Dialogue Systems](https://mlsanity.com/paper/2205.15060/) (2022)
- [Perceived Safety in Physical Human Robot Interaction -- A Survey](https://mlsanity.com/paper/2105.14499/) (2021)
- [Artificial Emotional Intelligence in Socially Assistive Robots for Older Adults: A Pilot Study](https://mlsanity.com/paper/2201.11167/) (2022)
- [Sympathy Begins with a Smile, Intelligence Begins with a Word: Use of Multimodal Features in Spoken Human-Robot Interaction](https://mlsanity.com/paper/1706.02757/) (2017)
- [AV-EmoDialog: Chat with Audio-Visual Users Leveraging Emotional Cues](https://mlsanity.com/paper/2412.17292/) (2024)
- [Creepy Technology: What Is It and How Do You Measure It?](https://mlsanity.com/paper/2102.07470/) (2021)
- [Do you feel safe with your robot? Factors Influencing Perceived Safety in Human-Robot Interaction based on Subjective and Objective Measures](https://mlsanity.com/paper/2106.05854/) (2021)
- [Human-Robot Interaction Conversational User Enjoyment Scale (HRI CUES)](https://mlsanity.com/paper/2405.01354/) (2024)
- [Emotional Tandem Robots: How Different Robot Behaviors Affect Human Perception While Controlling a Mobile Robot](https://mlsanity.com/paper/2403.03746/) (2024)
- [What Can You Say to a Robot? Capability Communication Leads to More Natural Conversations](https://mlsanity.com/paper/2502.01448/) (2025)

## Built on by (most cited first, 3 of 3)

- [Humanizing Machines: Rethinking LLM Anthropomorphism Through a Multi-Level Framework of Design](https://mlsanity.com/paper/2508.17573/) (2025)
- [Systematizing LLM Persona Design: A Four-Quadrant Technical Taxonomy for AI Companion Applications](https://mlsanity.com/paper/2511.02979/) (2025)
- [Back to the museum: Investigation of the acceptance of Android Andrea with and without emotion simulation in a museum](https://mlsanity.com/paper/2607.16428/) (2026)

## Abstract (arXiv)

Humanoid social robots are increasingly present in daily life, making sustained user engagement a critical factor for their effectiveness and acceptance. While prior work has often examined affective evaluations or anthropomorphic design, less is known about the relative influence of dynamic conversational qualities and perceived robot characteristics in determining a user's intention to re-engage with Large Language Model (LLM)-driven social robots. In this study, 68 participants interacted in open-ended conversations with the Nadine humanoid social robot, completing pre- and post-interaction surveys to assess changes in robot perception, conversational quality, and intention to re-engage. The results showed that verbal interaction significantly improved the robot's perceived characteristics, with statistically significant increases in pleasantness (p<.0001) and approachability (p<.0001), and a reduction in creepiness (p<.001). However, these affective changes were not strong and unique predictors of users' intention to re-engage in a multiple regression model. Instead, participants' perceptions of the interestingness (β=0.60, p<.001) and naturalness (β=0.31, p=0.015) of the robot's conversation emerged as the most significant and robust independent predictors of intention to re-engage. Overall, the results highlight that conversational quality, specifically perceived interestingness and naturalness, is the dominant driver of re-engagement, indicating that LLM-driven robot design should prioritize engaging, natural dialogue over affective impression management or anthropomorphic cues.