• DocumentCode
    718187
  • Title

    Understanding the unobservable population in call detail records through analysis of mobile phone user calling behavior: A case study of Greater Dhaka in Bangladesh

  • Author

    Arai, Ayumi ; Witayangkurn, Apichon ; Horanont, Teerayut ; Xiaowei Shao ; Shibasaki, Ryosuke

  • Author_Institution
    Center for Spatial Inf. Sci., Univ. of Tokyo, Tokyo, Japan
  • fYear
    2015
  • fDate
    23-27 March 2015
  • Firstpage
    207
  • Lastpage
    214
  • Abstract
    The understanding of mass population movements has greatly advanced with the rapid spread of ubiquitous devices. Anonymized call detail records (CDRs) for mobile phones have enabled us to not only trace individual trajectories but also approximate activity patterns, including significant locations such as homes and workplaces. The majority of studies analyzing CDRs attempt to utilize the mobility patterns of anonymized crowds to improve transportation and public health. This is quite reasonable because CDRs can capture the movements of people at given times and places, whereas general statistics usually account for a population based on their locations of residence. However, it has also been pointed out that there are discrepancies between the movements of people as observed through CDRs and those of an entire population in a given area. This is because CDRs only represent device users. In fact, we can never learn about the population that is unobservable through CDRs only by analyzing CDRs. Therefore, this study attempts to provide clues to help us understand the whereabouts of the unobservable population by analyzing two months of the CDRs for 58 volunteers with mobile device service from a major telecommunications company in combination with field survey data from Dhaka. We surveyed the personal and household attributes of mobile users in relation to their calling behavior. The analysis results show that per mobile user observed in CDRs, there is an average of roughly 2.4 to 2.8 unobservable people. Their age groups and gender composition are also provided. We find that male and female users exhibit opposite trends in call locations according to the presence of children within the household. In addition, based on field observations, we find that the location and time distributions of small children follow some specific routines. Our findings contribute to the understanding of the whereabouts of the unobservable population, the majority of whom are children and a- e considered to be vulnerable to disasters or infectious diseases but are difficult to locate through CDRs alone.
  • Keywords
    behavioural sciences; mobile handsets; social aspects of automation; statistical analysis; ubiquitous computing; Bangladesh; Greater Dhaka; call detail records; general statistics; mass population movements understanding; mobile phone user calling behavior analysis; unobservable population; Conferences; Market research; Mobile communication; Mobile handsets; Pervasive computing; Sociology; Statistics; CDRs; demographic attributes; mobile phone; sample bias;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing and Communications (PerCom), 2015 IEEE International Conference on
  • Conference_Location
    St. Louis, MO
  • Type

    conf

  • DOI
    10.1109/PERCOM.2015.7146530
  • Filename
    7146530