{"id":"https://openalex.org/W2903978737","doi":"https://doi.org/10.1609/aaai.v33i01.33017249","title":"A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection","display_name":"A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2903978737","doi":"https://doi.org/10.1609/aaai.v33i01.33017249","mag":"2903978737"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33017249","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017249","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4710/4588","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4710/4588","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059038918","display_name":"Penghui Wei","orcid":"https://orcid.org/0000-0002-8701-9833"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Penghui Wei","raw_affiliation_strings":["Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035983004","display_name":"Wenji Mao","orcid":"https://orcid.org/0000-0003-2323-5091"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenji Mao","raw_affiliation_strings":["Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005512011","display_name":"Guandan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guandan Chen","raw_affiliation_strings":["Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059038918"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":1.3301,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.85108898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"33","issue":"01","first_page":"7249","last_page":"7256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9986000061035156,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7797132730484009},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7314476370811462},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6556428670883179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6537287831306458},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.64188152551651},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5321150422096252},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5031749606132507},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43863773345947266},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4318467080593109},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.306862473487854},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11008498072624207}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7797132730484009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7314476370811462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6556428670883179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6537287831306458},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.64188152551651},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5321150422096252},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5031749606132507},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43863773345947266},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4318467080593109},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.306862473487854},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11008498072624207},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v33i01.33017249","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017249","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4710/4588","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33017249","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017249","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4710/4588","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3843286025","display_name":null,"funder_award_id":"71472175","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G523751891","display_name":null,"funder_award_id":"#71702181","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5658744965","display_name":null,"funder_award_id":"71702181","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6587632849","display_name":null,"funder_award_id":"#71621002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8208342437","display_name":null,"funder_award_id":"1 and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8558028238","display_name":null,"funder_award_id":"2016QY02D0305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G997903294","display_name":null,"funder_award_id":"71621002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2903978737.pdf","grobid_xml":"https://content.openalex.org/works/W2903978737.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1887364683","https://openalex.org/W1967807490","https://openalex.org/W2048195127","https://openalex.org/W2108646579","https://openalex.org/W2118463056","https://openalex.org/W2133564696","https://openalex.org/W2142213820","https://openalex.org/W2150850338","https://openalex.org/W2153579005","https://openalex.org/W2155027007","https://openalex.org/W2327805699","https://openalex.org/W2437771934","https://openalex.org/W2438911840","https://openalex.org/W2460159515","https://openalex.org/W2462365838","https://openalex.org/W2551396370","https://openalex.org/W2565166462","https://openalex.org/W2566287401","https://openalex.org/W2575422056","https://openalex.org/W2736601468","https://openalex.org/W2752262499","https://openalex.org/W2767245334","https://openalex.org/W2776652360","https://openalex.org/W2783256872","https://openalex.org/W2788810909","https://openalex.org/W2798367316","https://openalex.org/W2798624200","https://openalex.org/W2799140283","https://openalex.org/W2804311790","https://openalex.org/W2808114373","https://openalex.org/W2859594143","https://openalex.org/W2869686875","https://openalex.org/W2896081888","https://openalex.org/W2914457445","https://openalex.org/W2950879740","https://openalex.org/W2951274974","https://openalex.org/W2962707223","https://openalex.org/W2962767317","https://openalex.org/W2962795929","https://openalex.org/W2962939608","https://openalex.org/W2962958286","https://openalex.org/W2963403868","https://openalex.org/W2963811339","https://openalex.org/W2964230653","https://openalex.org/W2964308564","https://openalex.org/W4211186029","https://openalex.org/W4294170691","https://openalex.org/W4385245566","https://openalex.org/W6662776447","https://openalex.org/W6682575916","https://openalex.org/W6718565325","https://openalex.org/W6736960337","https://openalex.org/W6753084064","https://openalex.org/W7075355921"],"related_works":["https://openalex.org/W4319083788","https://openalex.org/W4306904961","https://openalex.org/W2949092679","https://openalex.org/W3204633138","https://openalex.org/W4298877126","https://openalex.org/W4287600613","https://openalex.org/W1473009882","https://openalex.org/W4385422125","https://openalex.org/W3114406058","https://openalex.org/W4385571929"],"abstract_inverted_index":{"Analyzing":[0],"public":[1],"attitudes":[2],"plays":[3],"an":[4,46],"important":[5],"role":[6],"in":[7,23,93],"opinion":[8],"mining":[9],"systems.":[10],"Stance":[11],"detection":[12,117],"aims":[13],"to":[14,58,69,137,154],"determine":[15],"from":[16,141],"a":[17,30,40,98,116,132],"text":[18,41],"whether":[19],"its":[20],"author":[21],"is":[22,38],"favor":[24],"of,":[25],"against,":[26],"or":[27],"neutral":[28],"towards":[29,48],"given":[31],"target.":[32],"One":[33],"challenge":[34],"of":[35,73,111],"this":[36,94],"task":[37],"that":[39,119,135,162],"may":[42],"not":[43],"explicitly":[44],"express":[45],"attitude":[47],"the":[49,71,89,168],"target,":[50],"but":[51],"existing":[52],"approaches":[53,65,80],"utilize":[54],"target":[55],"content":[56],"alone":[57],"build":[59],"models.":[60],"Moreover,":[61],"although":[62],"weakly":[63,104],"supervised":[64,105],"have":[66],"been":[67],"proposed":[68,164],"ease":[70],"burden":[72],"manually":[74],"annotating":[75],"largescale":[76],"training":[77],"data,":[78],"such":[79],"are":[81,151],"confronted":[82],"with":[83],"noisy":[84,139],"labeling":[85],"problem.":[86],"To":[87],"address":[88],"above":[90],"two":[91,112],"issues,":[92],"paper,":[95],"we":[96],"propose":[97],"Topic-Aware":[99],"Reinforced":[100],"Model":[101],"(TARM)":[102],"for":[103,127],"stance":[106,129],"detection.":[107],"Our":[108],"model":[109,165],"consists":[110],"complementary":[113],"components:":[114],"(1)":[115],"network":[118,134],"incorporates":[120],"target-related":[121],"topic":[122],"information":[123],"into":[124],"representation":[125],"learning":[126],"identifying":[128],"effectively;":[130],"(2)":[131],"policy":[133],"learns":[136],"eliminate":[138],"instances":[140],"auto-labeled":[142],"data":[143],"based":[144],"on":[145],"off-policy":[146],"reinforcement":[147],"learning.":[148],"Two":[149],"networks":[150],"alternately":[152],"optimized":[153],"improve":[155],"each":[156],"other\u2019s":[157],"performances.":[158],"Experimental":[159],"results":[160],"demonstrate":[161],"our":[163],"TARM":[166],"outperforms":[167],"state-of-the-art":[169],"approaches.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
