{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T07:58:50Z","timestamp":1780473530694,"version":"3.54.1"},"reference-count":124,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T00:00:00Z","timestamp":1671580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100019188","name":"HORIZON EUROPE Excellent Science","doi-asserted-by":"publisher","award":["823783"],"award-info":[{"award-number":["823783"]}],"id":[{"id":"10.13039\/100019188","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2022,12,21]]},"abstract":"<jats:p>Mood inference with mobile sensing data has been studied in ubicomp literature over the last decade. This inference enables context-aware and personalized user experiences in general mobile apps and valuable feedback and interventions in mobile health apps. However, even though model generalization issues have been highlighted in many studies, the focus has always been on improving the accuracies of models using different sensing modalities and machine learning techniques, with datasets collected in homogeneous populations. In contrast, less attention has been given to studying the performance of mood inference models to assess whether models generalize to new countries. In this study, we collected a mobile sensing dataset with 329K self-reports from 678 participants in eight countries (China, Denmark, India, Italy, Mexico, Mongolia, Paraguay, UK) to assess the effect of geographical diversity on mood inference models. We define and evaluate country-specific (trained and tested within a country), continent-specific (trained and tested within a continent), country-agnostic (tested on a country not seen on training data), and multi-country (trained and tested with multiple countries) approaches trained on sensor data for two mood inference tasks with population-level (non-personalized) and hybrid (partially personalized) models. We show that partially personalized country-specific models perform the best yielding area under the receiver operating characteristic curve (AUROC) scores of the range 0.78--0.98 for two-class (negative vs. positive valence) and 0.76--0.94 for three-class (negative vs. neutral vs. positive valence) inference. Further, with the country-agnostic approach, we show that models do not perform well compared to country-specific settings, even when models are partially personalized. We also show that continent-specific models outperform multi-country models in the case of Europe. Overall, we uncover generalization issues of mood inference models to new countries and how the geographical similarity of countries might impact mood inference.<\/jats:p>","DOI":"10.1145\/3569483","type":"journal-article","created":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T15:34:01Z","timestamp":1673451241000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":46,"title":["Generalization and Personalization of Mobile Sensing-Based Mood Inference Models"],"prefix":"10.1145","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5275-6585","authenticated-orcid":false,"given":"Lakmal","family":"Meegahapola","sequence":"first","affiliation":[{"name":"Idiap Research Institute &amp; EPFL, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0379-2018","authenticated-orcid":false,"given":"William","family":"Droz","sequence":"additional","affiliation":[{"name":"Idiap Research Institute, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0778-7662","authenticated-orcid":false,"given":"Peter","family":"Kun","sequence":"additional","affiliation":[{"name":"Aalborg University, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7214-5856","authenticated-orcid":false,"given":"Amalia","family":"de G\u00f6tzen","sequence":"additional","affiliation":[{"name":"Aalborg University, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5164-2391","authenticated-orcid":false,"given":"Chaitanya","family":"Nutakki","sequence":"additional","affiliation":[{"name":"Amrita Vishwa Vidyapeetham, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1546-0184","authenticated-orcid":false,"given":"Shyam","family":"Diwakar","sequence":"additional","affiliation":[{"name":"Amrita Vishwa Vidyapeetham, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2918-6780","authenticated-orcid":false,"given":"Salvador Ruiz","family":"Correa","sequence":"additional","affiliation":[{"name":"Instituto Potosino de Investigaci\u00f3n Cient\u00edfica y Tecnol\u00f3gica, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6737-6932","authenticated-orcid":false,"given":"Donglei","family":"Song","sequence":"additional","affiliation":[{"name":"Jilin University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9300-8180","authenticated-orcid":false,"given":"Hao","family":"Xu","sequence":"additional","affiliation":[{"name":"Jilin University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1583-6551","authenticated-orcid":false,"given":"Miriam","family":"Bidoglia","sequence":"additional","affiliation":[{"name":"London School of Economics and Political Science, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6135-9496","authenticated-orcid":false,"given":"George","family":"Gaskell","sequence":"additional","affiliation":[{"name":"London School of Economics and Political Science, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2331-3045","authenticated-orcid":false,"given":"Altangerel","family":"Chagnaa","sequence":"additional","affiliation":[{"name":"National University of Mongolia, Mongolia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4335-6608","authenticated-orcid":false,"given":"Amarsanaa","family":"Ganbold","sequence":"additional","affiliation":[{"name":"National University of Mongolia, Mongolia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2797-517X","authenticated-orcid":false,"given":"Tsolmon","family":"Zundui","sequence":"additional","affiliation":[{"name":"National University of Mongolia, Mongolia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6609-1572","authenticated-orcid":false,"given":"Carlo","family":"Caprini","sequence":"additional","affiliation":[{"name":"U-Hopper, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3089-977X","authenticated-orcid":false,"given":"Daniele","family":"Miorandi","sequence":"additional","affiliation":[{"name":"U-Hopper, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1874-1419","authenticated-orcid":false,"given":"Alethia","family":"Hume","sequence":"additional","affiliation":[{"name":"Universidad Cat\u00f3lica \"Nuestra Se\u00f1ora de la Asunci\u00f3n\", Paraguay"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0069-4287","authenticated-orcid":false,"given":"Jose Luis","family":"Zarza","sequence":"additional","affiliation":[{"name":"Universidad Cat\u00f3lica \"Nuestra Se\u00f1ora de la Asunci\u00f3n\", Paraguay"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7803-1067","authenticated-orcid":false,"given":"Luca","family":"Cernuzzi","sequence":"additional","affiliation":[{"name":"Universidad Cat\u00f3lica \"Nuestra Se\u00f1ora de la Asunci\u00f3n\", Paraguay"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9645-8627","authenticated-orcid":false,"given":"Ivano","family":"Bison","sequence":"additional","affiliation":[{"name":"University of Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7607-7587","authenticated-orcid":false,"given":"Marcelo Rodas","family":"Britez","sequence":"additional","affiliation":[{"name":"University of Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3788-0203","authenticated-orcid":false,"given":"Matteo","family":"Busso","sequence":"additional","affiliation":[{"name":"University of Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1121-0287","authenticated-orcid":false,"given":"Ronald","family":"Chenu-Abente","sequence":"additional","affiliation":[{"name":"University of Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8750-6498","authenticated-orcid":false,"given":"Can","family":"G\u00fcnel","sequence":"additional","affiliation":[{"name":"University of Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5903-6150","authenticated-orcid":false,"given":"Fausto","family":"Giunchiglia","sequence":"additional","affiliation":[{"name":"University of Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3320-2314","authenticated-orcid":false,"given":"Laura","family":"Schelenz","sequence":"additional","affiliation":[{"name":"University of T\u00fcbingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5488-2182","authenticated-orcid":false,"given":"Daniel","family":"Gatica-Perez","sequence":"additional","affiliation":[{"name":"Idiap Research Institute &amp; EPFL, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,1,11]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0266516"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3090051"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2017.11.016"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3179702"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2019.2925338"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.2196\/14567"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/02699930143000149"},{"key":"e_1_2_2_8_1","volume-title":"Nearest neighbor imputation algorithms: a critical evaluation. BMC medical informatics and decision making 16, 3","author":"Beretta Lorenzo","year":"2016","unstructured":"Lorenzo Beretta and Alessandro Santaniello. 2016. Nearest neighbor imputation algorithms: a critical evaluation. BMC medical informatics and decision making 16, 3 (2016), 197--208."},{"key":"e_1_2_2_9_1","unstructured":"Stuart JH Biddle et al. 2000. Emotion mood and physical activity. Physical activity and psychological well-being 63 (2000)."},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3161161"},{"key":"e_1_2_2_11_1","volume-title":"MoodHacker Mobile Web App With Email for Adults to Self-Manage Mild-to-Moderate Depression: Randomized Controlled Trial. JMIR mHealth uHealth 4, 1 (26","author":"Birney Amelia J","year":"2016","unstructured":"Amelia J Birney, Rebecca Gunn, Jeremy K Russell, and Dennis V Ary. 2016. MoodHacker Mobile Web App With Email for Adults to Self-Manage Mild-to-Moderate Depression: Randomized Controlled Trial. JMIR mHealth uHealth 4, 1 (26 Jan 2016), e8."},{"key":"e_1_2_2_12_1","volume-title":"Artificial intelligence safety and security","author":"Bostrom Nick","unstructured":"Nick Bostrom and Eliezer Yudkowsky. 2018. The ethics of artificial intelligence. In Artificial intelligence safety and security. Chapman and Hall\/CRC, 57--69."},{"key":"e_1_2_2_13_1","volume-title":"The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern recognition 30, 7","author":"Bradley Andrew P","year":"1997","unstructured":"Andrew P Bradley. 1997. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern recognition 30, 7 (1997), 1145--1159."},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/IEMBS.2011.6090412"},{"key":"e_1_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2750858.2805845"},{"key":"e_1_2_2_16_1","volume-title":"Is facial recognition too biased to be let loose? Nature 587, 7834","author":"Castelvecchi Davide","year":"2020","unstructured":"Davide Castelvecchi. 2020. Is facial recognition too biased to be let loose? Nature 587, 7834 (2020), 347--350."},{"key":"e_1_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11920-018-0954-3"},{"key":"e_1_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3380985"},{"key":"e_1_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3446382.3448361"},{"key":"e_1_2_2_21_1","unstructured":"Fran\u00e7ois Chollet et al. 2015. keras."},{"key":"e_1_2_2_22_1","volume-title":"Ethical issues in affective computing. The Oxford handbook of affective computing","author":"Cowie Roddy","year":"2015","unstructured":"Roddy Cowie. 2015. Ethical issues in affective computing. The Oxford handbook of affective computing (2015), 334--348."},{"key":"e_1_2_2_23_1","volume-title":"Suicidal thoughts and behaviors among adults aged 18 Years--United States","author":"Crosby Alex","year":"2008","unstructured":"Alex Crosby, Joseph Gfroerer, Beth Han, LaVonne Ortega, and Sharyn E Parks. 2011. Suicidal thoughts and behaviors among adults aged 18 Years--United States, 2008--2009. (2011)."},{"key":"e_1_2_2_24_1","volume-title":"Random Forests","author":"Cutler Adele","unstructured":"Adele Cutler, David Cutler, and John Stevens. 2011. Random Forests. Vol. 45. 157--176."},{"key":"e_1_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3149509"},{"key":"e_1_2_2_26_1","volume-title":"The mini-IPIP scales: tiny-yet-effective measures of the Big Five factors of personality. Psychological assessment 18, 2","author":"Donnellan M Brent","year":"2006","unstructured":"M Brent Donnellan, Frederick L Oswald, Brendan M Baird, and Richard E Lucas. 2006. The mini-IPIP scales: tiny-yet-effective measures of the Big Five factors of personality. Psychological assessment 18, 2 (2006), 192."},{"key":"e_1_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1222"},{"key":"e_1_2_2_28_1","volume-title":"LimeSurvey http:\/\/limesurvey.org: Visited","author":"Engard Nicole C","year":"2009","unstructured":"Nicole C Engard. 2009. LimeSurvey http:\/\/limesurvey.org: Visited: Summer 2009. (2009)."},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocx005"},{"key":"e_1_2_2_30_1","volume-title":"Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data. In 2016 IEEE Wireless Health (WH)","author":"Farhan Asma Ahmad","unstructured":"Asma Ahmad Farhan, Chaoqun Yue, Reynaldo Morillo, Shweta Ware, Jin Lu, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis, and Bing Wang. 2016. Behavior vs. introspection: refining prediction of clinical depression via smartphone sensing data. In 2016 IEEE Wireless Health (WH). IEEE, 1--8."},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2973425"},{"key":"e_1_2_2_32_1","volume-title":"Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychological bulletin 143, 2","author":"Franklin Joseph C","year":"2017","unstructured":"Joseph C Franklin, Jessica D Ribeiro, Kathryn R Fox, Kate H Bentley, Evan M Kleiman, Xieyining Huang, Katherine M Musacchio, Adam C Jaroszewski, Bernard P Chang, and Matthew K Nock. 2017. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychological bulletin 143, 2 (2017), 187."},{"key":"e_1_2_2_33_1","unstructured":"Fausto Giunchiglia. 2020. A Diversity-aware Internet When Technology Works for People.(2020)."},{"key":"e_1_2_2_34_1","unstructured":"Fausto Giunchiglia Ivano Bison Matteo Busso Ronald Chenu-Abente Marcelo Rodas Mattia Zeni Can Gunel Giuseppe Veltri Amalia De G\u00f6tzen Peter Kun Amarsanaa Ganbold Altangerel Chagnaa George Gaskell Sally Stares Miriam Bidoglia Luca Cernuzzi Alethia Hume Jose Luis Zarza Hao Xu Donglei Song Shyam Diwakar Chaitanya Nutakki Salvador Ruiz Correa Andrea-Rebeca Mendoza Lakmal Meegahapola and Daniel Gatica-Perez. 2022. A worldwide diversity pilot on daily routines and social practices (2020-2021). University of Trento Technical Report - DataScientia dataset descriptors. https:\/\/iris.unitn.it\/handle\/11572\/338382."},{"key":"e_1_2_2_35_1","volume-title":"How transport modes, the built and natural environments, and activities influence mood: A GPS smartphone app study. JOURNAL OF ENVIRONMENTAL PSYCHOLOGY 66 (DEC","author":"Glasgow Trevin E.","year":"2019","unstructured":"Trevin E. Glasgow, Huyen T. K. Le, E. Scott Geller, Yingling Fan, and Steve Hankey. 2019. How transport modes, the built and natural environments, and activities influence mood: A GPS smartphone app study. JOURNAL OF ENVIRONMENTAL PSYCHOLOGY 66 (DEC 2019)."},{"key":"e_1_2_2_36_1","volume-title":"Jinwoo Shin, and Sung-Ju Lee.","author":"Gong Taesik","year":"2021","unstructured":"Taesik Gong, Yewon Kim, Adiba Orzikulova, Yunxin Liu, Sung Ju Hwang, Jinwoo Shin, and Sung-Ju Lee. 2021. DAPPER: Performance Estimation of Domain Adaptation in Mobile Sensing. arXiv preprint arXiv:2111.11053 (2021)."},{"key":"e_1_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2917620"},{"key":"e_1_2_2_38_1","volume-title":"Retrieved","year":"2022","unstructured":"Google. 2022. Adapt your app by understanding what users are doing. Retrieved February 12, 2022 from https:\/\/developers.google.com\/location-context\/activity-recognition"},{"key":"e_1_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.paid.2013.12.012"},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10654-016-0149-3"},{"key":"e_1_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Patrick J Grother Mei L Ngan Kayee K Hanaoka et al. 2019. Face recognition vendor test part 3: demographic effects. (2019).","DOI":"10.6028\/NIST.IR.8280"},{"key":"e_1_2_2_42_1","volume-title":"Beyond relational demography: Time and the effects of surface-and deep-level diversity on work group cohesion","author":"Harrison David A","year":"1998","unstructured":"David A Harrison, Kenneth H Price, and Myrtle P Bell. 1998. Beyond relational demography: Time and the effects of surface-and deep-level diversity on work group cohesion. Academy of management journal 41, 1 (1998), 96--107."},{"key":"e_1_2_2_43_1","volume-title":"Ubiquitous Computing in the Workplace","author":"Hilty Lorenz M","unstructured":"Lorenz M Hilty. 2015. Ethical issues in ubiquitous computing---three technology assessment studies revisited. In Ubiquitous Computing in the Workplace. Springer, 45--60."},{"key":"e_1_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/1500879.1500888"},{"key":"e_1_2_2_45_1","volume-title":"Predicting negative emotions based on mobile phone usage patterns: an exploratory study. JMIR research protocols 5, 3","author":"Chin-Lun Hung Galen","year":"2016","unstructured":"Galen Chin-Lun Hung, Pei-Ching Yang, Chia-Chi Chang, Jung-Hsien Chiang, and Ying-Yeh Chen. 2016. Predicting negative emotions based on mobile phone usage patterns: an exploratory study. JMIR research protocols 5, 3 (2016), e5551."},{"key":"e_1_2_2_46_1","volume-title":"Psychological types","author":"Jung Carl","unstructured":"Carl Jung. 2016. Psychological types. Routledge."},{"key":"e_1_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2755661"},{"key":"e_1_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1123\/jsep.32.2.253"},{"key":"e_1_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.2196\/mental.4370"},{"key":"e_1_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351246"},{"key":"e_1_2_2_51_1","volume-title":"T test as a parametric statistic. Korean Journal of Anesthesiology 68 (11","author":"Kim Tae","year":"2015","unstructured":"Tae Kim. 2015. T test as a parametric statistic. Korean Journal of Anesthesiology 68 (11 2015), 540."},{"key":"e_1_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2013.00863"},{"key":"e_1_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2010.5560598"},{"key":"e_1_2_2_54_1","unstructured":"Dong Kyu Lee. 2016. Alternatives to P value: confidence interval and effect size. In Korean journal of anesthesiology."},{"key":"e_1_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.2196\/mental.8324"},{"key":"e_1_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3073864"},{"key":"e_1_2_2_57_1","volume-title":"Moodscope: Building a mood sensor from smartphone usage patterns. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 389--402.","author":"LiKamWa Robert","year":"2013","unstructured":"Robert LiKamWa, Yunxin Liu, Nicholas D Lane, and Lin Zhong. 2013. Moodscope: Building a mood sensor from smartphone usage patterns. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 389--402."},{"key":"e_1_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/2370216.2370270"},{"key":"e_1_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00261"},{"key":"e_1_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1300\/J046v16n04_03"},{"key":"e_1_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/SLT.2008.4777902"},{"key":"e_1_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3345609"},{"key":"e_1_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1080\/03069880801926400"},{"key":"e_1_2_2_64_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3045935"},{"key":"e_1_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448120"},{"key":"e_1_2_2_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3428361.3428463"},{"key":"e_1_2_2_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448120"},{"key":"e_1_2_2_68_1","unstructured":"Alan Mislove. 2010. Pulse of the nation: US mood throughout the day inferred from twitter. http:\/\/www.ccs.neu.edu\/home\/amis-love\/twittermood\/ (2010)."},{"key":"e_1_2_2_69_1","volume-title":"Ethics sheet for automatic emotion recognition and sentiment analysis. arXiv preprint arXiv:2109.08256","author":"Mohammad Saif M","year":"2021","unstructured":"Saif M Mohammad. 2021. Ethics sheet for automatic emotion recognition and sentiment analysis. arXiv preprint arXiv:2109.08256 (2021)."},{"key":"e_1_2_2_70_1","volume-title":"Personal sensing: understanding mental health using ubiquitous sensors and machine learning. Annual review of clinical psychology 13","author":"Mohr David C","year":"2017","unstructured":"David C Mohr, Mi Zhang, and Stephen M Schueller. 2017. Personal sensing: understanding mental health using ubiquitous sensors and machine learning. Annual review of clinical psychology 13 (2017), 23--47."},{"key":"e_1_2_2_71_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2017.04.004"},{"key":"e_1_2_2_72_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351233"},{"key":"e_1_2_2_73_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-93087-x"},{"key":"e_1_2_2_74_1","volume-title":"Gradient boosting machines, a tutorial. Frontiers in neurorobotics 7","author":"Natekin Alexey","year":"2013","unstructured":"Alexey Natekin and Alois Knoll. 2013. Gradient boosting machines, a tutorial. Frontiers in neurorobotics 7 (2013), 21."},{"key":"e_1_2_2_75_1","volume-title":"Retrieved","year":"2022","unstructured":"nationsonline. 2022. The Continents of the World. Retrieved May 15, 2022 from https:\/\/www.nationsonline.org\/oneworld\/continents.htm"},{"key":"e_1_2_2_76_1","doi-asserted-by":"publisher","DOI":"10.14201\/ADCAIJ2013242940"},{"key":"e_1_2_2_77_1","volume-title":"What is a support vector machine? Nature biotechnology 24, 12","author":"Noble William S","year":"2006","unstructured":"William S Noble. 2006. What is a support vector machine? Nature biotechnology 24, 12 (2006), 1565--1567."},{"key":"e_1_2_2_78_1","volume-title":"Retrieved","author":"Partnership","year":"2022","unstructured":"Partnership on AI. 2022. The Ethics of AI and Emotional Intelligence. Retrieved May 13, 2022 from https:\/\/partnershiponai.org\/paper\/the-ethics-of-ai-and-emotional-intelligence\/"},{"key":"e_1_2_2_79_1","volume-title":"Mental health of young people: a global public-health challenge. The Lancet 369, 9569","author":"Patel Vikram","year":"2007","unstructured":"Vikram Patel, Alan J Flisher, Sarah Hetrick, and Patrick McGorry. 2007. Mental health of young people: a global public-health challenge. The Lancet 369, 9569 (2007), 1302--1313."},{"key":"e_1_2_2_80_1","unstructured":"Fabian Pedregosa Ga\u00ebl Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron Weiss Vincent Dubourg et al. 2011. Scikit-Learn: Machine learning in Python. the Journal of machine Learning research 12 (2011) 2825--2830."},{"key":"e_1_2_2_81_1","doi-asserted-by":"crossref","unstructured":"Le Vy Phan Nick Modersitzki Kim K Gloystein and Sandrine M\u00fcller. 2022. Mobile Sensing Around the Globe: Considerations for Cross-Cultural Research. psyarxiv.com\/q8c7y","DOI":"10.31234\/osf.io\/q8c7y"},{"key":"e_1_2_2_82_1","volume-title":"The accuracy of passive phone sensors in predicting daily mood. Depression and anxiety 36, 1","author":"Pratap Abhishek","year":"2019","unstructured":"Abhishek Pratap, David C Atkins, Brenna N Renn, Michael J Tanana, Sean D Mooney, Joaquin A Anguera, and Patricia A Are\u00e1n. 2019. The accuracy of passive phone sensors in predicting daily mood. Depression and anxiety 36, 1 (2019), 72--81."},{"key":"e_1_2_2_83_1","unstructured":"John Pucher and Ralph Buehler. 2007. At the frontiers of cycling. Policy innovations in the Netherlands Denmark and Germany. (2007)."},{"key":"e_1_2_2_84_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07509-9_58"},{"key":"e_1_2_2_85_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hlpt.2021.01.002"},{"key":"e_1_2_2_86_1","volume-title":"Harris","author":"Rice Marnie E.","year":"2005","unstructured":"Marnie E. Rice and Grant T. Harris. 2005. Comparing Effect Sizes in Follow-Up Studies: ROC Area, Cohen's d, and r. Law and Human Behavior 29, 5 (01 Oct 2005), 615--620."},{"key":"e_1_2_2_87_1","doi-asserted-by":"publisher","DOI":"10.5694\/j.1326-5377.2007.tb01334.x"},{"key":"e_1_2_2_88_1","volume-title":"IJCAI 2001 workshop on empirical methods in artificial intelligence","volume":"3","author":"Irina","unstructured":"Irina Rish et al. 2001. An empirical study of the naive Bayes classifier. In IJCAI 2001 workshop on empirical methods in artificial intelligence, Vol. 3. 41--46."},{"key":"e_1_2_2_89_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1752-0606.2003.tb00386.x"},{"key":"e_1_2_2_90_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0077714"},{"key":"e_1_2_2_91_1","volume-title":"Nour Shewaikani, Hamzah Khawaldah, Sobuh Abu-Shanab, and Maysa Al-Hussaini.","author":"Saadeh Heba","year":"2021","unstructured":"Heba Saadeh, Reem Q. Al Fayez, Assem Al Refaei, Nour Shewaikani, Hamzah Khawaldah, Sobuh Abu-Shanab, and Maysa Al-Hussaini. 2021. Smartphone Use Among University Students During COVID-19 Quarantine: An Ethical Trigger. Frontiers in Public Health 9 (July 2021), 600134."},{"key":"e_1_2_2_92_1","volume-title":"Stress recognition using wearable sensors and mobile phones. In 2013 Humaine association conference on affective computing and intelligent interaction","author":"Sano Akane","unstructured":"Akane Sano and Rosalind W Picard. 2013. Stress recognition using wearable sensors and mobile phones. In 2013 Humaine association conference on affective computing and intelligent interaction. IEEE, 671--676."},{"key":"e_1_2_2_93_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2018.2797901"},{"key":"e_1_2_2_94_1","volume-title":"Empirical inference","author":"Schapire Robert E","unstructured":"Robert E Schapire. 2013. Explaining adaboost. In Empirical inference. Springer, 37--52."},{"key":"e_1_2_2_95_1","doi-asserted-by":"publisher","DOI":"10.1145\/3461702.3462595"},{"key":"e_1_2_2_96_1","volume-title":"Understanding People's Use of and Perspectives on Mood-Tracking Apps: Interview Study. JMIR mental health 8, 8","author":"Schueller Stephen M","year":"2021","unstructured":"Stephen M Schueller, Martha Neary, Jocelyn Lai, and Daniel A Epstein. 2021. Understanding People's Use of and Perspectives on Mood-Tracking Apps: Interview Study. JMIR mental health 8, 8 (2021), e29368."},{"key":"e_1_2_2_97_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-4560.1994.tb01196.x"},{"key":"e_1_2_2_98_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052618"},{"key":"e_1_2_2_99_1","volume-title":"Occupational stressors and the mental health of truckers. Issues in mental health nursing 31, 9","author":"Shattell Mona","year":"2010","unstructured":"Mona Shattell, Yorghos Apostolopoulos, Sevil S\u00f6nmez, and Mary Griffin. 2010. Occupational stressors and the mental health of truckers. Issues in mental health nursing 31, 9 (2010), 561--568."},{"key":"e_1_2_2_100_1","volume-title":"Multimodal emotion recognition in response to videos","author":"Soleymani Mohammad","year":"2011","unstructured":"Mohammad Soleymani, Maja Pantic, and Thierry Pun. 2011. Multimodal emotion recognition in response to videos. IEEE transactions on affective computing 3, 2 (2011), 211--223."},{"key":"e_1_2_2_101_1","doi-asserted-by":"publisher","DOI":"10.1145\/3329189.3329213"},{"key":"e_1_2_2_102_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmjsem-2020-000960"},{"key":"e_1_2_2_103_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.11.063"},{"key":"e_1_2_2_104_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpr.2021.102021"},{"key":"e_1_2_2_105_1","first-page":"206","article-title":"Identification of multiple intelligences with the Multiple Intelligence Profiling Questionnaire III","volume":"50","author":"Tirri Kirsi","year":"2008","unstructured":"Kirsi Tirri and Petri Nokelainen. 2008. Identification of multiple intelligences with the Multiple Intelligence Profiling Questionnaire III. Psychology Science 50, 2 (2008), 206.","journal-title":"Psychology Science"},{"key":"e_1_2_2_106_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.erap.2003.12.004"},{"key":"e_1_2_2_107_1","volume-title":"A Complete Guide to Sequential Feature Selection. Retrieved","author":"Verma Yugesh","year":"2022","unstructured":"Yugesh Verma. 2021. A Complete Guide to Sequential Feature Selection. Retrieved August 2, 2022 from https:\/\/analyticsindiamag.com\/a-complete-guide-to-sequential-feature-selection\/"},{"key":"e_1_2_2_108_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-57959-7"},{"key":"e_1_2_2_109_1","doi-asserted-by":"crossref","unstructured":"Fabian Wahle Tobias Kowatsch Elgar Fleisch Michael Rufer Steffi Weidt et al. 2016. Mobile sensing and support for people with depression: a pilot trial in the wild. JMIR mHealth and uHealth 4 3 (2016) e5960.","DOI":"10.2196\/mhealth.5960"},{"key":"e_1_2_2_110_1","doi-asserted-by":"publisher","DOI":"10.1145\/3491102.3501835"},{"key":"e_1_2_2_111_1","doi-asserted-by":"publisher","DOI":"10.1145\/2971648.2971740"},{"key":"e_1_2_2_112_1","doi-asserted-by":"publisher","DOI":"10.1145\/2632048.2632054"},{"key":"e_1_2_2_113_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00894"},{"key":"e_1_2_2_114_1","volume-title":"Retrieved","author":"Ward Johnny","year":"2020","unstructured":"Johnny Ward. 2020. How Many Continents In The World? 5,6,7? Retrieved May 15, 2022 from https:\/\/onestep4ward.com\/how-many-continents-in-the-world\/"},{"key":"e_1_2_2_115_1","volume-title":"Bonferroni correction. https:\/\/mathworld. wolfram. com\/","author":"Weisstein Eric W","year":"2004","unstructured":"Eric W Weisstein. 2004. Bonferroni correction. https:\/\/mathworld. wolfram. com\/ (2004)."},{"key":"e_1_2_2_116_1","volume-title":"Janardhan Rao Doppa, and Diane J Cook","author":"Wilson Garrett","year":"2022","unstructured":"Garrett Wilson, Janardhan Rao Doppa, and Diane J Cook. 2022. Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition. arXiv preprint arXiv:2207.04367 (2022)."},{"key":"e_1_2_2_117_1","volume-title":"Retrieved","year":"2022","unstructured":"Worldometer. 2022. 7 Continents. Retrieved May 15, 2022 from https:\/\/www.worldometers.info\/geography\/7-continents\/"},{"key":"e_1_2_2_118_1","first-page":"1","article-title":"Leveraging Collaborative-Filtering for Personalized Behavior Modeling: A Case Study of Depression Detection among College Students","volume":"5","author":"Xu Xuhai","year":"2021","unstructured":"Xuhai Xu, Prerna Chikersal, Janine M Dutcher, Yasaman S Sefidgar, Woosuk Seo, Michael J Tumminia, Daniella K Villalba, Sheldon Cohen, Kasey G Creswell, J David Creswell, et al. 2021. Leveraging Collaborative-Filtering for Personalized Behavior Modeling: A Case Study of Depression Detection among College Students. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, 1 (2021), 1--27.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_2_2_119_1","volume-title":"Gender and nation","author":"Yuval-Davis Nira","unstructured":"Nira Yuval-Davis. 2004. Gender and nation. Routledge."},{"key":"e_1_2_2_120_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21010052"},{"key":"e_1_2_2_121_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350957"},{"key":"e_1_2_2_122_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17176035"},{"key":"e_1_2_2_123_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2877847"},{"key":"e_1_2_2_124_1","doi-asserted-by":"crossref","unstructured":"James Zou and Londa Schiebinger. 2018. AI can be sexist and racist---it's time to make it fair.","DOI":"10.1038\/d41586-018-05707-8"}],"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\/3569483","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3569483","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T20:55:23Z","timestamp":1752612923000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569483"}},"subtitle":["An Analysis of College Students in Eight Countries"],"short-title":[],"issued":{"date-parts":[[2022,12,21]]},"references-count":124,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,12,21]]}},"alternative-id":["10.1145\/3569483"],"URL":"https:\/\/doi.org\/10.1145\/3569483","relation":{},"ISSN":["2474-9567"],"issn-type":[{"value":"2474-9567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,21]]},"assertion":[{"value":"2023-01-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}