{"id":"https://openalex.org/W4226139798","doi":"https://doi.org/10.1109/access.2022.3158975","title":"Injecting User Identity Into Pretrained Language Models for Document-Level Sentiment Classification","display_name":"Injecting User Identity Into Pretrained Language Models for Document-Level Sentiment Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226139798","doi":"https://doi.org/10.1109/access.2022.3158975"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3158975","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3158975","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733377.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733377.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000377914","display_name":"Xinlei Cao","orcid":"https://orcid.org/0000-0001-6854-2154"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinlei Cao","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002539019","display_name":"Jinyang Yu","orcid":"https://orcid.org/0000-0001-6015-2952"},"institutions":[{"id":"https://openalex.org/I4210132195","display_name":"Guangdong Province Environmental Monitoring Center","ror":"https://ror.org/03gfeke93","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210132195"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyang Yu","raw_affiliation_strings":["Center for ADR Monitoring of Guangdong, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Center for ADR Monitoring of Guangdong, Guangzhou, China","institution_ids":["https://openalex.org/I4210132195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100735881","display_name":"Yan Zhuang","orcid":"https://orcid.org/0000-0001-7351-377X"},"institutions":[{"id":"https://openalex.org/I2802939634","display_name":"Chinese PLA General Hospital","ror":"https://ror.org/04gw3ra78","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2802939634"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhuang","raw_affiliation_strings":["National Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, China","Medical Innovation Research Division, Medical Big Data Research Center, Chinese PLA General Hospital, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, China","institution_ids":["https://openalex.org/I2802939634"]},{"raw_affiliation_string":"Medical Innovation Research Division, Medical Big Data Research Center, Chinese PLA General Hospital, Beijing, China","institution_ids":["https://openalex.org/I2802939634"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000377914"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4588,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.84382407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"30157","last_page":"30167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9994000196456909,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9871000051498413,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8525055050849915},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.7812753915786743},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.7078616619110107},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.6994693279266357},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5476570725440979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5447233319282532},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.5309808850288391},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5029072165489197},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.45155346393585205},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.44794678688049316},{"id":"https://openalex.org/keywords/plug-in","display_name":"Plug-in","score":0.41248393058776855},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34612053632736206},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18702027201652527},{"id":"https://openalex.org/keywords/user-interface","display_name":"User interface","score":0.16471055150032043},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.10026630759239197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8525055050849915},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7812753915786743},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.7078616619110107},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6994693279266357},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5476570725440979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5447233319282532},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.5309808850288391},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5029072165489197},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.45155346393585205},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.44794678688049316},{"id":"https://openalex.org/C4924752","wikidata":"https://www.wikidata.org/wiki/Q184148","display_name":"Plug-in","level":2,"score":0.41248393058776855},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34612053632736206},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18702027201652527},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.16471055150032043},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.10026630759239197},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3158975","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3158975","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733377.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c520b50370154cada6ea4a39885a8cd5","is_oa":true,"landing_page_url":"https://doaj.org/article/c520b50370154cada6ea4a39885a8cd5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 30157-30167 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3158975","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3158975","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09733377.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320329835","display_name":"Chinese People\u2019s Liberation Army","ror":"https://ror.org/05tf9r976"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4226139798.pdf","grobid_xml":"https://content.openalex.org/works/W4226139798.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2064675550","https://openalex.org/W2194775991","https://openalex.org/W2242874043","https://openalex.org/W2250539671","https://openalex.org/W2250966211","https://openalex.org/W2251292973","https://openalex.org/W2470673105","https://openalex.org/W2514530580","https://openalex.org/W2525778437","https://openalex.org/W2537027648","https://openalex.org/W2563010554","https://openalex.org/W2604763608","https://openalex.org/W2776249353","https://openalex.org/W2788889673","https://openalex.org/W2899663614","https://openalex.org/W2908510526","https://openalex.org/W2938830017","https://openalex.org/W2962902802","https://openalex.org/W2963026768","https://openalex.org/W2963467630","https://openalex.org/W2964236337","https://openalex.org/W2965373594","https://openalex.org/W2970261805","https://openalex.org/W2980708516","https://openalex.org/W2987954551","https://openalex.org/W3011411500","https://openalex.org/W3011574394","https://openalex.org/W3088409176","https://openalex.org/W3117344805","https://openalex.org/W3121601851","https://openalex.org/W3148040514","https://openalex.org/W3156333129","https://openalex.org/W4292779060","https://openalex.org/W6727690538","https://openalex.org/W6732388730","https://openalex.org/W6732742072","https://openalex.org/W6736057607","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6755977528","https://openalex.org/W6757817989","https://openalex.org/W6761910064","https://openalex.org/W6765807869","https://openalex.org/W6766673545","https://openalex.org/W6778883912"],"related_works":["https://openalex.org/W2981957539","https://openalex.org/W2468279273","https://openalex.org/W4287378204","https://openalex.org/W47352601","https://openalex.org/W2545422590","https://openalex.org/W4240705470","https://openalex.org/W2945311252","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W631546281"],"abstract_inverted_index":{"This":[0],"paper":[1],"mainly":[2],"studies":[3,71],"the":[4,41,77,157],"combination":[5,78],"of":[6,46,61,79,132,166],"pre-trained":[7,21,80,134,192],"language":[8,22,81,135,193],"models":[9,23,82],"and":[10,83,103,105,122,137,171],"user":[11,53,64,84,101,127,180],"identity":[12,54,65,85,102,128,181],"information":[13,50],"for":[14,55,86],"document-level":[15,37],"sentiment":[16,38],"classification.":[17,39],"In":[18,175],"recent":[19],"years,":[20],"(PLMs)":[24],"such":[25,51],"as":[26,52],"BERT":[27],"have":[28,72],"achieved":[29],"state-of-the-art":[30,159],"results":[31],"on":[32,173],"many":[33],"NLP":[34],"applications,":[35],"including":[36],"On":[40],"other":[42],"hand,":[43],"a":[44,133],"collection":[45],"works":[47],"introduce":[48],"additional":[49],"better":[56,88],"text":[57],"modeling.":[58],"However,":[59],"most":[60,190],"them":[62],"inject":[63,126],"into":[66,129],"traditional":[67],"models,":[68],"while":[69],"few":[70],"been":[73],"conducted":[74],"to":[75,99,168],"study":[76],"even":[87],"performance.":[89],"To":[90],"address":[91],"this":[92,95],"issue,":[93],"in":[94,144],"paper,":[96],"we":[97,113],"propose":[98],"unite":[100],"PLMs":[104,150],"formulate":[106],"User-enhanced":[107],"Pre-trained":[108],"Language":[109],"Models":[110],"(U-PLMs).":[111],"Specifically,":[112],"demonstrate":[114],"two":[115,148],"simple":[116],"yet":[117],"effective":[118],"attempts,":[119],"i.e.":[120],"embedding-based":[121],"attention-based":[123],"personalization,":[124],"which":[125,185],"different":[130,141],"parts":[131],"model":[136],"provide":[138],"personalization":[139],"from":[140],"perspectives.":[142],"Experiments":[143],"three":[145],"datasets":[146],"with":[147,162,182,189],"backbone":[149],"show":[151],"that":[152],"our":[153,177],"proposed":[154],"methods":[155,178],"outperform":[156],"best":[158],"baseline":[160],"method":[161],"an":[163],"absolute":[164],"improvement":[165],"up":[167],"3%,":[169],"2.8%,":[170],"2.2%":[172],"accuracy.":[174],"addition,":[176],"encode":[179],"plugin":[183],"modules,":[184],"are":[186],"fully":[187],"compatible":[188],"auto-encoding":[191],"models.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}