{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T13:19:34Z","timestamp":1767705574717,"version":"3.41.0"},"reference-count":43,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2018,1,8]],"date-time":"2018-01-08T00:00:00Z","timestamp":1515369600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100005825","name":"USDA NIFA","doi-asserted-by":"crossref","award":["2017-67007-26150"],"award-info":[{"award-number":["2017-67007-26150"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2018,1,8]]},"abstract":"<jats:p>With the rapid growth in smartphone usage, it has been more and more important to understand the patterns of mobile data consumption by users. In this paper, we present an empirical study of the correlation between user mobility and app usage patterns. In particular, we focus on users' moving speed as the key mobility metric, and try to answer the following question: are there any notable relations between moving speed and the app usage patterns? Our study is based on a real-world, large-scale dataset of 2G phone network data request records. A critical challenge was that the raw data records are rather coarse-grained. More specifically, unlike GPS traces, the exact locations of users were not readily available. We inferred users' approximate locations according to their interactions with nearby cell towers, whose locations were known. We proposed a novel method to filter out noises and perform reliable speed estimation. We verify our methodology with out of sample data and show its improvement in speed estimation accuracy. We then examined several aspects of mobile data usage patterns, including the data volume, the access frequency, and the app categories, to reveal the correlation between these patterns and users' moving speed. Experimental results based on our large-scale real-world datasets revealed that users under different mobility categories not only have different smartphone usage motivations but also have different ways of using their smartphones.<\/jats:p>","DOI":"10.1145\/3161171","type":"journal-article","created":{"date-parts":[[2018,1,9]],"date-time":"2018-01-09T13:26:11Z","timestamp":1515504371000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Inferring Correlation between User Mobility and App Usage in Massive Coarse-grained Data Traces"],"prefix":"10.1145","volume":"1","author":[{"given":"Zheng","family":"Lu","sequence":"first","affiliation":[{"name":"University of Tennessee, Knoxville, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunhe","family":"Feng","sequence":"additional","affiliation":[{"name":"University of Tennessee, Knoxville, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjun","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Tennessee, Knoxville, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolin","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, Jiangsu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Cao","sequence":"additional","affiliation":[{"name":"University of Tennessee, Knoxville, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,1,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2638728.2641703"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/17489725.2015.1066515"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/13658816.2012.692791"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2037373.2037383"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Eunjoon Cho Seth A Myers and Jure Leskovec. 2011. Friendship and mobility: user movement in location-based social networks. In KDD. 1082--1090. Eunjoon Cho Seth A Myers and Jure Leskovec. 2011. Friendship and mobility: user movement in location-based social networks. In KDD. 1082--1090.","DOI":"10.1145\/2020408.2020579"},{"volume-title":"Ericsson Mobility Report. (Feb","year":"2016","key":"e_1_2_1_6_1"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2181196.2181199"},{"key":"e_1_2_1_8_1","unstructured":"Sean Gillies et al. 2013. Shapely. (2013). https:\/\/pypi.python.org\/pypi\/Shapely [Online; accessed &lt;today&gt;]. Sean Gillies et al. 2013. Shapely. (2013). https:\/\/pypi.python.org\/pypi\/Shapely [Online; accessed &lt;today&gt;]."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2517351.2517367"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2014.02.011"},{"volume-title":"Emilio Frazzoli, and Marta C Gonz\u00e1lez.","year":"2013","author":"Jiang Shan","key":"e_1_2_1_11_1"},{"key":"e_1_2_1_12_1","unstructured":"Eric Jones Travis Oliphant Pearu Peterson etal 2001. SciPy: Open source scientific tools for Python. (2001). http:\/\/www.scipy.org\/ [Online; accessed &lt;today&gt;]. Eric Jones Travis Oliphant Pearu Peterson et al. 2001. SciPy: Open source scientific tools for Python. (2001). http:\/\/www.scipy.org\/ [Online; accessed &lt;today&gt;]."},{"volume-title":"CRAWDAD dataset intel\/placelab (v. 2004-12-17). Downloaded from http:\/\/crawdad.org\/intel\/placelab\/20041217\/placelab. (Dec","year":"2004","author":"LaMarca Anthony","key":"e_1_2_1_13_1"},{"volume-title":"Proceedings of the 6th International COnference. ACM, 26","year":"2010","author":"Lee Kyunghan","key":"e_1_2_1_14_1"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2674005.2674982"},{"key":"e_1_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Lei Meng Shu Liu and Aaron D Striegel. 2014. Analyzing the impact of proximity location and personality on smartphone usage. In INFOCOM WKSHPS. 293--298. Lei Meng Shu Liu and Aaron D Striegel. 2014. Analyzing the impact of proximity location and personality on smartphone usage. In INFOCOM WKSHPS. 293--298.","DOI":"10.1109\/INFCOMW.2014.6849247"},{"volume-title":"Path Estimation Using Cellular Handover. Bachelor of Science Thesis","author":"Mosny Math\u00e9 Young","key":"e_1_2_1_18_1"},{"volume-title":"SMARTPHONES: SO MANY APPS, SO MUCH TIME. (July","year":"2014","key":"e_1_2_1_19_1"},{"key":"e_1_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Anastasios Noulas Salvatore Scellato Cecilia Mascolo and Massimiliano Pontil. 2011. An Empirical Study of Geographic User Activity Patterns in Foursquare. In ICWSM. 570--573. Anastasios Noulas Salvatore Scellato Cecilia Mascolo and Massimiliano Pontil. 2011. An Empirical Study of Geographic User Activity Patterns in Foursquare. In ICWSM. 570--573.","DOI":"10.1609\/icwsm.v5i1.14175"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2014.6958169"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1689239.1689243"},{"volume-title":"Introducing CloudLab: Scientific Infrastructure for Advancing Cloud Architectures and Applications. USENIX;login","year":"2014","author":"Ricci Robert","key":"e_1_2_1_23_1"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1080\/01441640500361108"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CSE.2009.312"},{"key":"e_1_2_1_26_1","doi-asserted-by":"crossref","unstructured":"M Zubair Shafiq Lusheng Ji Alex X Liu Jeffrey Pang and Jia Wang. 2012. Characterizing geospatial dynamics of application usage in a 3G cellular data network. In INFOCOM. 1341--1349. M Zubair Shafiq Lusheng Ji Alex X Liu Jeffrey Pang and Jia Wang. 2012. Characterizing geospatial dynamics of application usage in a 3G cellular data network. In INFOCOM. 1341--1349.","DOI":"10.1109\/INFCOM.2012.6195497"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2014.07.011"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1108\/9781781902882-041"},{"volume-title":"Number of apps available in leading app stores as of","year":"2015","key":"e_1_2_1_29_1"},{"key":"e_1_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Leon Stenneth Ouri Wolfson Philip S Yu and Bo Xu. 2011. Transportation mode detection using mobile phones and GIS information. In GIS. 54--63. Leon Stenneth Ouri Wolfson Philip S Yu and Bo Xu. 2011. Transportation mode detection using mobile phones and GIS information. In GIS. 54--63.","DOI":"10.1145\/2093973.2093982"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.4108\/icst.pervasivehealth.2011.246060"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.4108\/icst.collaboratecom.2012.250450"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2627534.2627553"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2010.5625188"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/APWCS.2010.18"},{"volume-title":"Transportation Research Board 93rd Annual Meeting.","year":"2014","author":"Wang Tingting","key":"e_1_2_1_36_1"},{"volume-title":"Pattern Recognition (ICPR), 2012 21st International Conference on. IEEE, 573--576","year":"2012","author":"Widhalm Peter","key":"e_1_2_1_37_1"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-015-9598-x"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/2068816.2068847"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMSNETS.2014.6734892"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2307636.2307648"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2014.2381512"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2016.7524464"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/1658373.1658374"}],"container-title":["Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3161171","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3161171","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,29]],"date-time":"2025-06-29T15:20:44Z","timestamp":1751210444000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3161171"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1,8]]},"references-count":43,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2018,1,8]]}},"alternative-id":["10.1145\/3161171"],"URL":"https:\/\/doi.org\/10.1145\/3161171","relation":{},"ISSN":["2474-9567"],"issn-type":[{"type":"electronic","value":"2474-9567"}],"subject":[],"published":{"date-parts":[[2018,1,8]]},"assertion":[{"value":"2017-02-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-10-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-01-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}