{"id":"https://openalex.org/W2970868452","doi":"https://doi.org/10.18653/v1/w19-5036","title":"Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning","display_name":"Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2970868452","doi":"https://doi.org/10.18653/v1/w19-5036","mag":"2970868452"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-5036","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5036","pdf_url":"https://www.aclweb.org/anthology/W19-5036.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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-5036.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046502677","display_name":"Hassan Alhuzali","orcid":"https://orcid.org/0000-0002-0935-0774"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Hassan Alhuzali","raw_affiliation_strings":["National Centre for Text Mining School of Computer Science, The University of Manchester, United Kingdom"],"affiliations":[{"raw_affiliation_string":"National Centre for Text Mining School of Computer Science, The University of Manchester, United Kingdom","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077976343","display_name":"Sophia Ananiadou","orcid":"https://orcid.org/0000-0002-4097-9191"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sophia Ananiadou","raw_affiliation_strings":["National Centre for Text Mining School of Computer Science, The University of Manchester, United Kingdom"],"affiliations":[{"raw_affiliation_string":"National Centre for Text Mining School of Computer Science, The University of Manchester, United Kingdom","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046502677"],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":null,"apc_paid":null,"fwci":2.6006,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.92200446,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"339","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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/T11644","display_name":"Spam and Phishing Detection","score":0.989799976348877,"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/T11943","display_name":"Pharmacovigilance and Adverse Drug Reactions","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.7724611163139343},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7487401962280273},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.7081189155578613},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6942087411880493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6618257761001587},{"id":"https://openalex.org/keywords/drug-reaction","display_name":"Drug reaction","score":0.6290044784545898},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6278941631317139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5279300212860107},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47827112674713135},{"id":"https://openalex.org/keywords/adverse-drug-reaction","display_name":"Adverse drug reaction","score":0.45472943782806396},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.420564740896225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4168432354927063},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.21113553643226624},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.20470762252807617},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11898660659790039},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08347636461257935}],"concepts":[{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.7724611163139343},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7487401962280273},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.7081189155578613},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6942087411880493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6618257761001587},{"id":"https://openalex.org/C2993432071","wikidata":"https://www.wikidata.org/wiki/Q45959","display_name":"Drug reaction","level":3,"score":0.6290044784545898},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6278941631317139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5279300212860107},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47827112674713135},{"id":"https://openalex.org/C2780542314","wikidata":"https://www.wikidata.org/wiki/Q45959","display_name":"Adverse drug reaction","level":3,"score":0.45472943782806396},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.420564740896225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4168432354927063},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.21113553643226624},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.20470762252807617},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11898660659790039},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08347636461257935},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/w19-5036","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5036","pdf_url":"https://www.aclweb.org/anthology/W19-5036.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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire/8fe6c5c5-6f50-4d5e-aba6-01886a9b31fb","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/8fe6c5c5-6f50-4d5e-aba6-01886a9b31fb","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Alhuzali, H & Ananiadou, S 2019, Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning. in Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning. pp. 339. https://doi.org/10.18653/v1/W19-5036","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/7212a4af-0c77-4498-9b5a-26c65ec7dc6e","is_oa":true,"landing_page_url":"https://research.manchester.ac.uk/en/publications/7212a4af-0c77-4498-9b5a-26c65ec7dc6e","pdf_url":"https://aclanthology.org/W19-5036.pdf","source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Alhuzali, H & Ananiadou, S 2019, 'Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning', pp. 339. < https://www.aclweb.org/anthology/W19-5036 >","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.18653/v1/w19-5036","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5036","pdf_url":"https://www.aclweb.org/anthology/W19-5036.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 18th BioNLP Workshop and Shared Task","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.550000011920929,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309370","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2970868452.pdf","grobid_xml":"https://content.openalex.org/works/W2970868452.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W107610923","https://openalex.org/W177032395","https://openalex.org/W1522301498","https://openalex.org/W1809871100","https://openalex.org/W1904365287","https://openalex.org/W1934253021","https://openalex.org/W2007628554","https://openalex.org/W2024862171","https://openalex.org/W2064675550","https://openalex.org/W2069010240","https://openalex.org/W2071478164","https://openalex.org/W2110646369","https://openalex.org/W2115535574","https://openalex.org/W2133564696","https://openalex.org/W2153401380","https://openalex.org/W2153579005","https://openalex.org/W2171469118","https://openalex.org/W2250243742","https://openalex.org/W2460863069","https://openalex.org/W2546651658","https://openalex.org/W2574184737","https://openalex.org/W2750747353","https://openalex.org/W2779179495","https://openalex.org/W2787404918","https://openalex.org/W2883897757","https://openalex.org/W2896457183","https://openalex.org/W2900341241","https://openalex.org/W2907473500","https://openalex.org/W2916132663","https://openalex.org/W2927746189","https://openalex.org/W2955854688","https://openalex.org/W2963026768","https://openalex.org/W2963341956","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2970352191","https://openalex.org/W3106003309","https://openalex.org/W4294170691","https://openalex.org/W4301054811"],"related_works":["https://openalex.org/W2376885761","https://openalex.org/W2995438986","https://openalex.org/W2398395680","https://openalex.org/W2365386954","https://openalex.org/W2377282230","https://openalex.org/W2348194333","https://openalex.org/W2352744048","https://openalex.org/W2370505849","https://openalex.org/W2347501567","https://openalex.org/W3030394802"],"abstract_inverted_index":{"The":[0],"availability":[1],"of":[2,25,109,124,138],"large-scale":[3],"and":[4,32,39,126,150,161],"real-time":[5],"data":[6],"on":[7,44],"social":[8,49,77,113],"media":[9,78,114],"has":[10],"motivated":[11],"research":[12],"into":[13],"adverse":[14],"drug":[15],"reactions":[16],"(ADRs).":[17],"ADR":[18,74],"classification":[19],"helps":[20],"to":[21,72,85,102,106,171],"identify":[22],"negative":[23,51],"effects":[24],"drugs,":[26],"which":[27],"can":[28,166],"guide":[29],"health":[30],"professionals":[31],"pharmaceutical":[33],"companies":[34],"in":[35,48,76,88,112,119,146],"making":[36],"medications":[37],"safer":[38],"advocating":[40],"patients'":[41],"safety.":[42],"Based":[43],"the":[45,94,104,107,135,142,147],"observation":[46],"that":[47,64,163],"media,":[50],"sentiment":[52,66,87],"is":[53,82,131],"frequently":[54],"expressed":[55],"towards":[56],"ADRs,":[57],"this":[58],"study":[59],"presents":[60],"a":[61],"neural":[62],"model":[63,105,165],"combines":[65],"analysis":[67],"with":[68,121,158],"transfer":[69,100,129],"learning":[70,101,130],"techniques":[71],"improve":[73],"detection":[75],"postings.":[79,115],"Our":[80],"system":[81],"firstly":[83],"trained":[84],"classify":[86],"tweets":[89],"concerning":[90],"current":[91,143],"affairs,":[92],"using":[93],"SemEval17-task4A":[95,148],"corpus.":[96],"We":[97,116,154],"then":[98],"apply":[99],"adapt":[103],"task":[108],"detecting":[110],"ADRs":[111],"show":[117,162],"that,":[118],"combination":[120],"rich":[122],"representations":[123],"words":[125],"their":[127],"contexts,":[128],"beneficial,":[132],"especially":[133],"given":[134],"large":[136],"degree":[137],"vocabulary":[139],"overlap":[140],"between":[141],"affairs":[144],"posts":[145,151],"corpus":[149],"about":[152],"ADRs.":[153],"compare":[155],"our":[156,164],"results":[157],"previous":[159],"approaches,":[160],"outperform":[167],"them":[168],"by":[169],"up":[170],"3%":[172],"F-score.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7}],"updated_date":"2026-04-07T14:57:38.498316","created_date":"2025-10-10T00:00:00"}