So far, most research investigating the predictability of human behavior, such as mobility and social interactions, has focused mainly on the exploitation of sensor data. However, sensor data can be difficult to capture the subjective motivations behind the individuals' behavior. Understanding personal context (e.g., where one is and what they are doing) can greatly increase predictability. The main limitation is that human input is often missing or inaccurate. The goal of this paper is to identify factors that influence the quality of responses when users are asked about their current context. We find that two key factors influence the quality of responses: user reaction time and completion time. These factors correlate with various exogenous causes (e.g., situational context, time of day) and endogenous causes (e.g., procrastination attitude, mood). In turn, we study how these two factors impact the quality of responses.

Factors Impacting the Quality of User Answers on Smartphones / Bison, Ivano; Zhao, Haonan. - 3456:(2023), pp. 208-213. (Intervento presentato al convegno HHAI 2023 tenutosi a Munich, Germany nel 26th-27th June 2023).

Factors Impacting the Quality of User Answers on Smartphones

Ivano Bison
Primo
;
Haonan Zhao
Ultimo
2023-01-01

Abstract

So far, most research investigating the predictability of human behavior, such as mobility and social interactions, has focused mainly on the exploitation of sensor data. However, sensor data can be difficult to capture the subjective motivations behind the individuals' behavior. Understanding personal context (e.g., where one is and what they are doing) can greatly increase predictability. The main limitation is that human input is often missing or inaccurate. The goal of this paper is to identify factors that influence the quality of responses when users are asked about their current context. We find that two key factors influence the quality of responses: user reaction time and completion time. These factors correlate with various exogenous causes (e.g., situational context, time of day) and endogenous causes (e.g., procrastination attitude, mood). In turn, we study how these two factors impact the quality of responses.
2023
Proceedings of the Workshops at the Second International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI 2023)
Aachen, Germany
RWTH Aachen
Bison, Ivano; Zhao, Haonan
Factors Impacting the Quality of User Answers on Smartphones / Bison, Ivano; Zhao, Haonan. - 3456:(2023), pp. 208-213. (Intervento presentato al convegno HHAI 2023 tenutosi a Munich, Germany nel 26th-27th June 2023).
File in questo prodotto:
File Dimensione Formato  
2023 Factors Impacting the Quality of User print.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Creative commons
Dimensione 983.77 kB
Formato Adobe PDF
983.77 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/391411
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact