Torkamaan, Helma; Ziegler, Jürgen:
Exploring chatbot user interfaces for mood measurement : A study of validity and user experience
In: Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers - UbiComp/ISWC 2020; Virtual, Online; Mexico; 12 - 17 September 2020 - New York: Association for Computing Machinery (ACM), 2020, S. 135 - 138
2020Buchaufsatz/Kapitel in Tagungsband
InformatikFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Informatik » Interaktive Systeme / Interaktionsdesign
Titel in Englisch:
Exploring chatbot user interfaces for mood measurement : A study of validity and user experience
Autor*in:
Torkamaan, HelmaUDE
GND
1259555046
LSF ID
58176
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Ziegler, JürgenUDE
GND
1015876811
LSF ID
3881
ORCID
0000-0001-9603-5272ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
Scopus ID
Sprache des Textes:
Englisch
Schlagwort, Thema:
affect grid ; chatbot ; conversational ESM ; mood tracking ; PANAS

Abstract in Englisch:

With the growth of interactive text or voice-enabled systems, such as intelligent personal assistants and chatbots, it is now possible to easily measure a user's mood using a conversation-based interaction instead of traditional questionnaires. However, it is still unclear if such mood measurements would be valid, akin to traditional measures, and user-engaging. Using smartphones, we compare in this paper two of the most popular traditional measures of mood: International PANAS-Short Form (I-PANAS-SF) and Affect Grid. For each of these measures, we then investigate the validity of mood measurement with a modified, chatbot-based user interface design. Our preliminary results suggest that some mood measures may not be resilient to modifications and that their alteration could lead to invalid, if not meaningless results. This exploratory paper then presents and discusses four voice-based mood tracker designs and summarizes user perception of and satisfaction with these tools. © 2020 Owner/Author.