{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,3]],"date-time":"2026-05-03T23:48:19Z","timestamp":1777852099819,"version":"3.51.4"},"reference-count":47,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2018,9,19]],"date-time":"2018-09-19T00:00:00Z","timestamp":1537315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2019,12]]},"abstract":"<jats:p>Binge drinking is a severe health problem faced by many US colleges and universities. College students often post drinking-related text and images on social media, portraying their alcohol use as socially desirable. In this project, we investigated the feasibility of mining the heterogeneous data (e.g. text, images, and videos) on Facebook to identify drinking-related contents. We manually annotated 4266 posts during 21 October 2011 and 3 November 2014 from \u201cI\u2019m Shmacked\u201d group on Facebook, where 511 posts were drinking-related. Our machine learning models show that by combining heterogeneous data types, we were able to identify drinking-related posts with an F1-score of 0.81. Prediction models built on text data were more reliable compared to those built on image and video data for predicting drinking-related contents. As the first step of our efforts in this direction, this feasibility study showed promise toward unleashing the potential of mining social media to identify students who binge drink.<\/jats:p>","DOI":"10.1177\/1460458218798084","type":"journal-article","created":{"date-parts":[[2018,9,19]],"date-time":"2018-09-19T10:04:48Z","timestamp":1537351488000},"page":"1756-1767","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["A feasibility study on identifying drinking-related contents in Facebook through mining heterogeneous data"],"prefix":"10.1177","volume":"25","author":[{"given":"Omar","family":"ElTayeby","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Todd","family":"Eaglin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malak","family":"Abdullah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Burlinson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwen","family":"Dou","sequence":"additional","affiliation":[{"name":"The University of North Carolina at Charlotte, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lixia","family":"Yao","sequence":"additional","affiliation":[{"name":"Mayo Clinic, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2018,9,19]]},"reference":[{"key":"bibr1-1460458218798084","first-page":"13","volume":"41","author":"Engs R","year":"1994","journal-title":"J Alcohol Drug Educ"},{"key":"bibr2-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1080\/07448480209595713"},{"key":"bibr3-1460458218798084","doi-asserted-by":"publisher","DOI":"10.15288\/jsads.2009.s16.12"},{"key":"bibr4-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1080\/07448480109595709"},{"issue":"2","key":"bibr5-1460458218798084","first-page":"2","volume":"5","author":"Fournier AK","year":"2011","journal-title":"Cyberpsychology"},{"key":"bibr6-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1111\/j.1465-3362.2010.00277.x"},{"key":"bibr7-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1037\/a0032097"},{"key":"bibr8-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1093\/alcalc\/agq103"},{"issue":"4","key":"bibr9-1460458218798084","first-page":"149","volume":"52","author":"Foote J","year":"2004","journal-title":"J Am Coll Health"},{"key":"bibr10-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1016\/j.jadohealth.2010.01.001"},{"key":"bibr11-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1111\/j.1083-6101.2008.01432.x"},{"key":"bibr12-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1177\/0146167208320061"},{"key":"bibr13-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2008.12.024"},{"key":"bibr14-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1177\/1557988310394341"},{"key":"bibr15-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1001\/archpediatrics.2008.528"},{"key":"bibr16-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1057\/jphp.2013.45"},{"key":"bibr17-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1093\/alcalc\/agt174"},{"key":"bibr18-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1001\/archpediatrics.2011.180"},{"key":"bibr19-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2013.07.060"},{"key":"bibr20-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2010.04.017"},{"key":"bibr21-1460458218798084","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.2503"},{"key":"bibr22-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1080\/10810730.2010.514032"},{"key":"bibr23-1460458218798084","volume-title":"Online policy adaptation for ensemble algorithms","author":"Dimitrakakis C","year":"2002"},{"key":"bibr24-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1007\/s11892-015-0584-7"},{"key":"bibr25-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2011.07.002"},{"key":"bibr26-1460458218798084","volume-title":"AAAI-98 workshop on learning for text categorization","author":"McCallum A","year":"1998"},{"issue":"12","key":"bibr27-1460458218798084","first-page":"2913","volume":"7","author":"Xu B","year":"2012","journal-title":"JCP"},{"key":"bibr28-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-34747-9_18"},{"key":"bibr29-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1007\/BFb0026683"},{"key":"bibr30-1460458218798084","volume-title":"ICML proceedings of the sixteenth international conference on machine learning","author":"Joachims T","year":"1999"},{"key":"bibr31-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1145\/1367497.1367510"},{"key":"bibr32-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1145\/2134254.2134276"},{"key":"bibr33-1460458218798084","doi-asserted-by":"publisher","DOI":"10.3115\/1699510.1699543"},{"key":"bibr34-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1109\/72.788646"},{"key":"bibr35-1460458218798084","first-page":"3371","volume":"11","author":"Vincent P","year":"2010","journal-title":"J Mach Learn Res"},{"key":"bibr36-1460458218798084","volume-title":"Artificial intelligence: a guide to intelligent systems","author":"Negnevitsky M.","year":"2005"},{"key":"bibr37-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-3223-4_12"},{"key":"bibr38-1460458218798084","volume-title":"Natural language processing with Python","author":"Bird S","year":"2009"},{"key":"bibr39-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-60045-1_38"},{"key":"bibr40-1460458218798084","volume-title":"A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization","author":"Joachims T.","year":"1996"},{"key":"bibr41-1460458218798084","first-page":"2825","volume":"12","author":"Pedregosa F","year":"2011","journal-title":"J Mach Learn Res"},{"key":"bibr42-1460458218798084","first-page":"993","volume":"3","author":"Blei DM","year":"2003","journal-title":"J Mach Learn Res"},{"key":"bibr43-1460458218798084","volume-title":"Proceedings of the 25th international conference on neural information processing systems","author":"Krizhevsky A","year":"2012"},{"key":"bibr44-1460458218798084","unstructured":"Hsu C-W, Chang C-C, Lin C-J. A practical guide to support vector classification, 2003, https:\/\/www.csie.ntu.edu.tw\/~cjlin\/papers\/guide\/guide.pdf"},{"key":"bibr45-1460458218798084","unstructured":"Sato I, Nakagawa H. Rethinking collapsed variational Bayes inference for LDA. arXiv: 1206.6435, 2012."},{"key":"bibr46-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2008.2007853"},{"key":"bibr47-1460458218798084","doi-asserted-by":"publisher","DOI":"10.1504\/IJKESDP.2011.039875"}],"container-title":["Health Informatics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1460458218798084","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/1460458218798084","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1460458218798084","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T22:30:28Z","timestamp":1777501828000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/1460458218798084"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,19]]},"references-count":47,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["10.1177\/1460458218798084"],"URL":"https:\/\/doi.org\/10.1177\/1460458218798084","relation":{},"ISSN":["1460-4582","1741-2811"],"issn-type":[{"value":"1460-4582","type":"print"},{"value":"1741-2811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,19]]}}}