When algorithms create personas from social media data, the personas can become noxious via automatically including toxic comments.
To investigate how users perceive such personas, we conducted a 2 × 2 user experiment with 496 participants that showed participants toxic and non-toxic versions of data-driven personas.
We found that participants gave higher credibility, likability, empathy, similarity, and willingness-to-use scores to non-toxic personas. Also, gender affected toxicity perceptions in that female toxic data-driven personas scored lower in likability, empathy, and similarity than their male counterparts.
Female participants gave higher perceptions scores to non-toxic personas and lower scores to toxic personas than male participants. We discuss implications from our research for designing data-driven personas.
Salminen, J., Jung, S. G., Santos, J. M., and Jansen, B. J. (2021) Toxic Text in Personas: An Experiment on User Perceptions. AIS Transactions on Human-Computer Interaction. 13(4), Paper 4.