{"id":"https://openalex.org/W2757953333","doi":"https://doi.org/10.18653/v1/d17-1241","title":"Multi-View Unsupervised User Feature Embedding for Social Media-based Substance Use Prediction","display_name":"Multi-View Unsupervised User Feature Embedding for Social Media-based Substance Use Prediction","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2757953333","doi":"https://doi.org/10.18653/v1/d17-1241","mag":"2757953333"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1241","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1241","pdf_url":"https://www.aclweb.org/anthology/D17-1241.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D17-1241.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010781360","display_name":"Tao Ding","orcid":"https://orcid.org/0000-0002-7590-0172"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tao Ding","raw_affiliation_strings":["Department of Information Systems University of Maryland, Baltimore County"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems University of Maryland, Baltimore County","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081714379","display_name":"Warren K. Bickel","orcid":"https://orcid.org/0000-0002-1048-7372"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]},{"id":"https://openalex.org/I5716644","display_name":"Carilion Clinic","ror":"https://ror.org/02rsjh069","country_code":"US","type":"funder","lineage":["https://openalex.org/I5716644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Warren K. Bickel","raw_affiliation_strings":["Addiction Recovery Research Center Virginia Tech Carilion Research Institute"],"affiliations":[{"raw_affiliation_string":"Addiction Recovery Research Center Virginia Tech Carilion Research Institute","institution_ids":["https://openalex.org/I5716644","https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048111120","display_name":"Shimei Pan","orcid":"https://orcid.org/0000-0002-5989-8543"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shimei Pan","raw_affiliation_strings":["Department of Information Systems University of Maryland, Baltimore County"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems University of Maryland, Baltimore County","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010781360"],"corresponding_institution_ids":["https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":12.0907,"has_fulltext":true,"cited_by_count":43,"citation_normalized_percentile":{"value":0.98508705,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2275","last_page":"2284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7900124788284302},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6595996022224426},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6312806606292725},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6207994222640991},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6148170828819275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6118864417076111},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5612467527389526},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.511370837688446},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4563584327697754},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43780308961868286},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32692983746528625},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09643429517745972}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7900124788284302},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6595996022224426},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6312806606292725},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6207994222640991},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6148170828819275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6118864417076111},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5612467527389526},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.511370837688446},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4563584327697754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43780308961868286},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32692983746528625},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09643429517745972},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d17-1241","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1241","pdf_url":"https://www.aclweb.org/anthology/D17-1241.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1241","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1241","pdf_url":"https://www.aclweb.org/anthology/D17-1241.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2757953333.pdf","grobid_xml":"https://content.openalex.org/works/W2757953333.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W28576867","https://openalex.org/W165525898","https://openalex.org/W1206398332","https://openalex.org/W1523385540","https://openalex.org/W1684832230","https://openalex.org/W1779879527","https://openalex.org/W1880262756","https://openalex.org/W1903768102","https://openalex.org/W1978528347","https://openalex.org/W1999192586","https://openalex.org/W2002715976","https://openalex.org/W2006207187","https://openalex.org/W2013912476","https://openalex.org/W2020341183","https://openalex.org/W2052635433","https://openalex.org/W2057979354","https://openalex.org/W2062280179","https://openalex.org/W2071207147","https://openalex.org/W2072878461","https://openalex.org/W2087054552","https://openalex.org/W2088795865","https://openalex.org/W2095048077","https://openalex.org/W2100235303","https://openalex.org/W2100495367","https://openalex.org/W2101324110","https://openalex.org/W2107789863","https://openalex.org/W2116787917","https://openalex.org/W2117897759","https://openalex.org/W2119595472","https://openalex.org/W2131744502","https://openalex.org/W2142674578","https://openalex.org/W2153803020","https://openalex.org/W2154868463","https://openalex.org/W2208848684","https://openalex.org/W2251297356","https://openalex.org/W2338708958","https://openalex.org/W2441043356","https://openalex.org/W2512549881","https://openalex.org/W2574650772","https://openalex.org/W2915177913","https://openalex.org/W3023057568"],"related_works":["https://openalex.org/W3196155444","https://openalex.org/W3209574120","https://openalex.org/W3087576162","https://openalex.org/W4287665842","https://openalex.org/W3210156800","https://openalex.org/W4285260836","https://openalex.org/W4323060038","https://openalex.org/W3046775127","https://openalex.org/W3123344745","https://openalex.org/W4367692580"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,44],"demonstrate":[4,65],"how":[5],"the":[6,66],"state-of-the-art":[7],"machine":[8],"learning":[9,49,73],"and":[10,83,108,137],"text":[11],"mining":[12],"techniques":[13],"can":[14],"be":[15],"used":[16],"to":[17,34,40,51,74,86],"build":[18],"effective":[19],"social":[20,60,131],"media-based":[21],"substance":[22,28,138],"use":[23,29,107],"detection":[24],"systems.":[25],"Since":[26],"a":[27,37,55,129],"ground":[30],"truth":[31],"is":[32],"difficult":[33],"obtain":[35],"on":[36,91],"large":[38,56],"scale,":[39],"maximize":[41],"system":[42,88],"performance,":[43],"explore":[45],"different":[46],"unsupervised":[47,59,71],"feature":[48,72],"methods":[50],"take":[52],"advantage":[53],"of":[54,58,68,115],"amount":[57],"media":[61,132],"data.":[62],"We":[63],"also":[64,124],"benefit":[67],"using":[69],"multi-view":[70],"combine":[75],"heterogeneous":[76],"user":[77],"information":[78],"such":[79],"as":[80],"Facebook":[81],"\"likes\"":[82],"\"status":[84],"updates\"":[85],"enhance":[87],"performance.":[89],"Based":[90],"our":[92,94],"evaluation,":[93],"best":[95],"models":[96],"achieved":[97],"86%":[98],"AUC":[99],"for":[100,105,110],"predicting":[101],"tobacco":[102],"use,":[103,113],"81%":[104],"alcohol":[106],"84%":[109],"illicit":[111],"drug":[112],"all":[114],"which":[116],"significantly":[117],"outperformed":[118],"existing":[119],"methods.":[120],"Our":[121],"investigation":[122],"has":[123],"uncovered":[125],"interesting":[126],"relations":[127],"between":[128],"user's":[130],"behavior":[133],"(e.g.,":[134],"word":[135],"usage)":[136],"use.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":1}],"updated_date":"2026-01-16T23:16:36.188383","created_date":"2025-10-10T00:00:00"}