  Chatbots are often designed to mimic social roles attributed to humans.
However, little is known about the impact on user's perceptions of using
language that fails to conform to the associated social role. Our research
draws on sociolinguistic theory to investigate how a chatbot's language choices
can adhere to the expected social role the agent performs within a given
context. In doing so, we seek to understand whether chatbots design should
account for linguistic register. This research analyzes how register
differences play a role in shaping the user's perception of the human-chatbot
interaction. Ultimately, we want to determine whether register-specific
language influences users' perceptions and experiences with chatbots. We
produced parallel corpora of conversations in the tourism domain with similar
content and varying register characteristics and evaluated users' preferences
of chatbot's linguistic choices in terms of appropriateness, credibility, and
user experience. Our results show that register characteristics are strong
predictors of user's preferences, which points to the needs of designing
chatbots with register-appropriate language to improve acceptance and users'
perceptions of chatbot interactions.
