Toxic text in personas: An experiment on user perceptions

Autor: Salminen, J., Jung, S. - G., Santos, J. M., Jansen, B. J.
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Popis: 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. info:eu-repo/semantics/publishedVersion
Databáze: OpenAIRE