Understanding behaviours in context using mobile sensing

被引:0
|
作者
Gabriella M. Harari
Samuel D. Gosling
机构
[1] Stanford University,Department of Communication
[2] The University of Texas at Austin,Department of Psychology
[3] University of Melbourne,School of Psychological Science
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Mobile sensing refers to the collection of methods by which researchers derive measures of human behaviours and contexts from the onboard sensors and logs found in smartphones, wearables and smart home devices. By tracking real-world behaviours in their natural contexts automatically, unobtrusively, continuously and in detail over extended periods of time, mobile sensing can help researchers to realize the potential of ecological approaches to psychology. In this Review, we consider how mobile sensing presents new opportunities for understanding behaviours in context and review illustrative findings from mobile sensing studies in psychology in three areas of research: social behaviours in physical and digital contexts, mobility behaviours in spatial contexts, and activities in digital contexts. In doing so, we highlight themes in the existing research and demonstrate the capabilities of mobile sensing, while evaluating how far mobile sensing has come in delivering on the promise of ecological approaches. To guide future mobile sensing research in psychology, we conclude with a research agenda focused on conceptual and measurement issues, pursuing explanatory and predictive research, and overcoming technical and practical barriers.
引用
收藏
页码:767 / 779
页数:12
相关论文
共 50 条
  • [21] Indexicality: Understanding Mobile Human-Computer Interaction in Context
    Kjeldskov, Jesper
    Paay, Jeni
    ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION, 2010, 17 (04)
  • [22] Understanding Mobile Search Task Relevance and User Behaviour in Context
    Aliannejadi, Mohammad
    Harvey, Morgan
    Costa, Luca
    Pointon, Matthew
    Crestani, Fabio
    PROCEEDINGS OF THE 2019 CONFERENCE ON HUMAN INFORMATION INTERACTION AND RETRIEVAL (CHIIR'19), 2019, : 143 - 151
  • [23] A Stochastic Game for Privacy Preserving Context Sensing on Mobile Phone
    Wang, Wei
    Zhang, Qian
    2014 PROCEEDINGS IEEE INFOCOM, 2014, : 2328 - 2336
  • [24] Context-Awareness for Mobile Sensing: A Survey and Future Directions
    Yueruer, Oezguer
    Liu, Chi Harold
    Sheng, Zhengguo
    Leung, Victor C. M.
    Moreno, Wilfrido
    Leung, Kin K.
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (01): : 68 - 93
  • [25] Understanding mobile learning adoption in higher education An empirical investigation in the context of the mobile library
    Gan, Chunmei
    Li, Hongxiu
    Liu, Yong
    ELECTRONIC LIBRARY, 2017, 35 (05): : 846 - 860
  • [26] Understanding the Relationship between Requirements and Context Elements in Mobile Collaboration
    Ochoa, Sergio
    Alarcon, Rosa
    Guerrero, Luis
    HUMAN-COMPUTER INTERACTION, PT III: AMBIENT, UBIQUITOUS AND INTELLIGENT INTERACTION, 2009, 5612 : 67 - +
  • [27] Context-aware computing for mobile crowd sensing: A survey
    Vahdat-Nejad, Hamed
    Asani, Elham
    Mahmoodian, Zohreh
    Mohseni, Mohammad Hossein
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 99 : 321 - 332
  • [28] Adaptive and Energy Efficient Context Representation Framework in Mobile Sensing
    Yurur, Ozgur
    Labrador, Miguel
    Moreno, Wilfrido
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2014, 13 (08) : 1681 - 1693
  • [29] Understanding tourist behavior using large-scale mobile sensing approach: A case study of mobile phone users in Japan
    Phithakkitnukoon, Santi
    Horanont, Teerayut
    Witayangkurn, Apichon
    Siri, Raktida
    Sekimoto, Yoshihide
    Shibasaki, Ryosuke
    PERVASIVE AND MOBILE COMPUTING, 2015, 18 : 18 - 39
  • [30] Image Understanding using Geometric Context
    Zhang, Xiaochun
    Liu, Chuancai
    NINTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2017), 2017, 10420