{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T18:31:02Z","timestamp":1778697062206,"version":"3.51.4"},"reference-count":33,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2016,6,6]],"date-time":"2016-06-06T00:00:00Z","timestamp":1465171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japanese Ministry of Education, Culture, Sports, Science and Technology"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>With the rapid spread of mobile devices, call detail records (CDRs) from mobile phones provide more opportunities to incorporate dynamic aspects of human mobility in addressing societal issues. However, it has been increasingly observed that CDR data are not always representative of the population under study because it only includes device users alone. To understand the discrepancy between the population captured by CDRs and the general population, we profile principal populations of CDRs by analyzing routines based on time spent at key locations and compare these data with those of the general population. We employ a topic model to estimate typical routines of mobile phone users using CDRs as topics. The routines are extracted from field survey data and compared between those of the general population and mobile phone users. We found that there are two main population groups of mobile phone users in Dhaka: males engaged in an income-generating activity at a specific location other than home and females performing household tasks and spending most of their time at home. We determine that CDRs tend to omit students, who form a significant component of the Dhaka population.<\/jats:p>","DOI":"10.3390\/ijgi5060085","type":"journal-article","created":{"date-parts":[[2016,6,6]],"date-time":"2016-06-06T10:47:38Z","timestamp":1465210058000},"page":"85","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Comparative Perspective of Human Behavior Patterns to Uncover Ownership Bias among Mobile Phone Users"],"prefix":"10.3390","volume":"5","author":[{"given":"Ayumi","family":"Arai","sequence":"first","affiliation":[{"name":"Earth Observation Data Integration and Fusion Research Initiative, University of Tokyo, 7-3-1, Hongo, Bunkyo, Tokyo 113-8656, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zipei","family":"Fan","sequence":"additional","affiliation":[{"name":"Graduate School of Engineering, University of Tokyo, 7-3-1, Hongo, Bunkyo, Tokyo 113-8656, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dunstan","family":"Matekenya","sequence":"additional","affiliation":[{"name":"Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryosuke","family":"Shibasaki","sequence":"additional","affiliation":[{"name":"Center for Spatial Information Science, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,6,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wesolowski, A., Eagle, N., Noor, A.M., Snow, R.W., and Buckee, C.O. 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