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Understanding Public Perception of Robots using Social Media

2019 - present



Supervised by

Prof. Austin Toombs

CCILAB, Purdue University 

My role:

HCI researcher

Research methodologies:

observation, online form data analysis

Project Description

As robots engage more in society in various forms, it is important to understand the public perception of robots. In this poster, we focus on a campus-centric subreddit (/r/purdue) to explore online discourse about delivery robots on the university campus. We specifically identify how people share their experiences with robots and how people perceive robots in society by analyzing Reddit posts. In so doing, we raise existing concerns about the robots which give insights into acceptance and sociability in human-robot interaction (HRI).


With this project, we address how social media can give insights into acceptance and sociability in HRI. Although the main role of starship robots is to deliver food to customers, people considered the robots not only as service providers, but as adorable mascots, vulnerable friends, aggressive gangs, or troublemakers. As the robots had become members of society in some shape or form, they reshaped the socio-cultural norms. We noted that most of the posts we analyzed were created by people who might not have directly interacted with the robots (i.e., order food from Starship) but were affected by the robots on campus. This implies the importance of understanding the public perception of robots who are not the main user directly interacting with the robot but have concerns about the robots on campus. 

Research Aim

  • Examine the emergent behavior occurring around delivery robots 

  • Explore how people describe their experience with delivery robots in online communities

  • Discover design guidelines for delivery robots based on analyzing online discussions


  • Lee, A., &  Toombs, A. (2020). Robots on Campus: Understanding Public Perception of Robots using Social Media.  Conference Companion Publication of the 2020 on Computer Supported Cooperative Work and Social Computing (CSCW). pp. 305-309.  DOI: 10.1145/3406865.3418321

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