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 are considered to be vulnerable to disasters or infectious diseases but are difficult to locate through CDRs alone.

Mobile phones are arguably one of the most prolific sources of large-scale human mobility data. The availability of this data has generated a massive body of research focused on understanding the dynamics and patterns of human mobility. However, it is increasingly evident that additional value can be derived from such data. This paper proposes a novel approach for understanding the attributes of mobile users by analyzing calling behavior derived from field survey data, in combination with call detail records (CDRs). Our survey reveals distinctive traits in calling behavior that correspond to user attributes. Analysis results demonstrate that frequent call locations, the variability in call time distributions, and the locations from which calls are made around midday are all keys to distinguishing gender. In addition, the location of calls initiated during the morning hours is a key to analyzing income levels for males.