Chatbots language design: the influence of language variation on user experience

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chaves, Ana Paula, Egbert, Jesse, Hocking, Toby, Doerry, Eck, Gerosa, Marco Aurelio
Format: Preprint
Veröffentlicht: 2021
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866914648169644032
author Chaves, Ana Paula
Egbert, Jesse
Hocking, Toby
Doerry, Eck
Gerosa, Marco Aurelio
author_facet Chaves, Ana Paula
Egbert, Jesse
Hocking, Toby
Doerry, Eck
Gerosa, Marco Aurelio
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2101_11089
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Chatbots language design: the influence of language variation on user experience
Chaves, Ana Paula
Egbert, Jesse
Hocking, Toby
Doerry, Eck
Gerosa, Marco Aurelio
Human-Computer Interaction
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.
title Chatbots language design: the influence of language variation on user experience
topic Human-Computer Interaction
url https://arxiv.org/abs/2101.11089