ABSTRACT
With the development of technology, mobile and wearable devices can obtain many different kinds of real-time activities from users. In social domains, the sharing of real-time activities is proved to help users to understand the current state of others and promote social relationships. However, most studies focused on real-time simple activities sharing, and the willingness of sharing real-time daily activities has not been fully studied. In this paper, we conduct an in-situ study to explore the willingness of sharing real-time daily activities among friends and study the factors that could influence sharing willingness. We find that daily activity types, friend types, location types, time periods, and participants’ privacy attitude classifications could influence sharing willingness. Our findings provide a basis for real-time communication systems to support the sharing of different types of daily activities. Furthermore, we present some design implications to better support real-time daily activities sharing.
Acknowledgments
We would like to thank all the participants for all the time and energy they have contributed to this research.
Notes
1. Fetion: http://feixin.10086.cn/.
2. American Time Use Survey Lexicon. Retrieved from: http://www.bls.gov/tus/home.htm.
3. American Time Use Survey Data Dictionary. Retrieved from: http://www.bls.gov/tus/home.htm.
Additional information
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Notes on contributors
Ling Chen
Ling Chen is an Associate Professor in the College of Computer Science and Technology, Zhejiang University, China, where he received his Ph.D. in computer science in 2004. His research interests include ubiquitous computing, location-aware computing, HCI and data mining.
Miaomiao Dong
Miaomiao Dong is a PhD student in the College of Computer Science and Technology, Zhejiang University, China. Her research interests mainly focus on human-computer interaction.
Liwen Wang
Liwen Wang is a PhD student in the College of Computer Science and Technology, Zhejiang University, China. Her research interests mainly focus on human-computer interaction in LBS.
Gencai Chen
Gencai Chen is a Professor in the College of Computer Science and Technology, Zhejiang University, China. His research interests include location-aware computing, HCI, database management systems and data mining.