{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T19:52:52Z","timestamp":1780084372526,"version":"3.54.0"},"reference-count":27,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:00:00Z","timestamp":1606089600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61772147 and 61100150"],"award-info":[{"award-number":["61772147 and 61100150"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"University Innovation Team Construction Project of Guangdong Province","award":["2015KCXTD014"],"award-info":[{"award-number":["2015KCXTD014"]}]},{"name":"Guangzhou City Bureau of Cooperative Innovation Project","award":["1201610005"],"award-info":[{"award-number":["1201610005"]}]},{"name":"Guangdong Province Natural Science Foundation of Major Basic Research and Cultivation Project","award":["2015A030308016"],"award-info":[{"award-number":["2015A030308016"]}]},{"name":"Social Science Foundation of Guangdong, China","award":["GD19CSH03"],"award-info":[{"award-number":["GD19CSH03"]}]},{"name":"Research Project of Guangzhou Education Bureau","award":["1201620222"],"award-info":[{"award-number":["1201620222"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2021,1,31]]},"abstract":"<jats:p>Happiness is a hot topic in academic circles. The study of happiness involves many disciplines, such as philosophy, psychology, sociology, and economics. However, there are few studies on the quantitative analysis of the factors affecting happiness. In this article, we used the well-known World Values Survey Wave 6 (WV6) dataset to quantitatively analyze the happiness of 57 countries with Big Data techniques. First, we obtained the seven most important factors by constructing happiness decision trees for each country. Calculating the frequencies of these factors, we obtained the 17 most important indicators for the prediction of happiness in the world. Then, we selected five representative countries, namely, Sweden, Japan, India, China, and the USA, and analyzed the indicators with the random forest method. We identified different patterns of factors that influence happiness in different countries. This study is a successful attempt to apply data mining technology in the social sciences, and the results are of practical significance.<\/jats:p>","DOI":"10.1145\/3412497","type":"journal-article","created":{"date-parts":[[2020,11,25]],"date-time":"2020-11-25T04:55:24Z","timestamp":1606280124000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["The Transnational Happiness Study with Big Data Technology"],"prefix":"10.1145","volume":"20","author":[{"given":"Lingxi","family":"Peng","sequence":"first","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haohuai","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yangang","family":"Nie","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Xie","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Tang","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Luo","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,11,23]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11205-015-0936-3"},{"key":"e_1_2_2_2_1","volume-title":"Intelligence 56","author":"Boris Nikolaev","year":"2016"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0024431"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.95.3.542"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1037\/0022-3514.57.6.1069"},{"key":"e_1_2_2_6_1","volume-title":"Myers and Ed Diener","author":"David","year":"1995"},{"key":"e_1_2_2_7_1","unstructured":"Sumner Larry Wayne. 1996. Welfare Happiness and Ethics. New York: Oxford Univ. Press.  Sumner Larry Wayne. 1996. Welfare Happiness and Ethics. New York: Oxford Univ. Press."},{"key":"e_1_2_2_8_1","volume-title":"Monica Sie Dhian Ho, and Astrid de Vries","author":"Veenhoven Ruut","year":"1993"},{"key":"e_1_2_2_9_1","doi-asserted-by":"crossref","unstructured":"Lingxi Peng Wenbin Chen Wubai Zhou Fufang Li Jin Yang and Jiandong Zhang. 2016. An immune-inspired semi-supervised algorithm for breast cancer diagnosis. Computer Methods and Programs in Biomedicine 134 (2016) 259--265.  Lingxi Peng Wenbin Chen Wubai Zhou Fufang Li Jin Yang and Jiandong Zhang. 2016. An immune-inspired semi-supervised algorithm for breast cancer diagnosis. Computer Methods and Programs in Biomedicine 134 (2016) 259--265.","DOI":"10.1016\/j.cmpb.2016.07.020"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-013-9932-9"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2019148"},{"key":"e_1_2_2_12_1","volume-title":"Causes and correlates of happiness","author":"Michael Argyle"},{"key":"e_1_2_2_13_1","unstructured":"Yann Algan Elizabeth Beasley Florian Guyot Kazuhito Higa Fabrice Murtin and Claudia Senik. 2016. Big Data measures of well-being: Evidence from a Google well-being index in the United States. OECD Statistics Working Papers.  Yann Algan Elizabeth Beasley Florian Guyot Kazuhito Higa Fabrice Murtin and Claudia Senik. 2016. Big Data measures of well-being: Evidence from a Google well-being index in the United States. OECD Statistics Working Papers."},{"key":"e_1_2_2_14_1","volume-title":"AAAI Spring Symposium Series 2016, AAAI Spring Symposium Series. 362--368","author":"Kido Takashi","year":"2016"},{"key":"e_1_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2010.08.011"},{"key":"e_1_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.10.006"},{"key":"e_1_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-06245-7"},{"key":"e_1_2_2_18_1","volume-title":"Retrieved","year":"2014"},{"key":"e_1_2_2_19_1","unstructured":"World Values Survey. 2014. Retrieved June 29 2019 from http:\/\/www.worldvaluessurvey.org\/wvs.jsp.  World Values Survey. 2014. Retrieved June 29 2019 from http:\/\/www.worldvaluessurvey.org\/wvs.jsp."},{"key":"e_1_2_2_20_1","volume-title":"Entropy 18","author":"Grzymala-Busse J.","year":"2016"},{"key":"e_1_2_2_21_1","volume-title":"International Journal of Computer Network 8 Information Security 8","author":"Koshal Jashan","year":"2012"},{"key":"e_1_2_2_22_1","volume-title":"Pattern Recognition 60","author":"Kyoungok Kim","year":"2016"},{"key":"e_1_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.11.010"},{"key":"e_1_2_2_24_1","doi-asserted-by":"crossref","unstructured":"Nantian Huang Guobo Lu and Dianguo Xu. 2016. A permutation importance-based feature selection method for short-term electricity load forecasting using random forest. Energies 9 (2016) 767.  Nantian Huang Guobo Lu and Dianguo Xu. 2016. A permutation importance-based feature selection method for short-term electricity load forecasting using random forest. Energies 9 (2016) 767.","DOI":"10.3390\/en9100767"},{"key":"e_1_2_2_25_1","volume-title":"Mirko Guarnera, and Sebastiano Battiato.","author":"Rav\u00ec R. Daniele","year":"2016"},{"key":"e_1_2_2_26_1","volume-title":"Random forest for ordinal responses. Computational Statistics and Data Analysis 96, (C","author":"Janitza Silke","year":"2016"},{"issue":"2106","key":"e_1_2_2_27_1","first-page":"1","article-title":"r2VIM: A new variable selection method for random forests in genome-wide association studies","volume":"9","author":"Szymczak Silke","year":"2016","journal-title":"BioData Mining"}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3412497","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3412497","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:25:02Z","timestamp":1750195502000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3412497"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,23]]},"references-count":27,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1,31]]}},"alternative-id":["10.1145\/3412497"],"URL":"https:\/\/doi.org\/10.1145\/3412497","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"value":"2375-4699","type":"print"},{"value":"2375-4702","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,23]]},"assertion":[{"value":"2020-02-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-07-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-11-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}