{"id":"https://openalex.org/W2798717312","doi":"https://doi.org/10.18653/v1/p18-1235","title":"A Helping Hand: Transfer Learning for Deep Sentiment Analysis","display_name":"A Helping Hand: Transfer Learning for Deep Sentiment Analysis","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2798717312","doi":"https://doi.org/10.18653/v1/p18-1235","mag":"2798717312"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-1235","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1235","pdf_url":"https://www.aclweb.org/anthology/P18-1235.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P18-1235.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088720980","display_name":"Xin Dong","orcid":"https://orcid.org/0000-0001-8727-8088"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xin Dong","raw_affiliation_strings":["Rutgers University New Brunswick, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085818578","display_name":"Gerard de Melo","orcid":"https://orcid.org/0000-0002-2930-2059"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gerard de Melo","raw_affiliation_strings":["Rutgers University New Brunswick, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088720980"],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":6.6003,"has_fulltext":true,"cited_by_count":54,"citation_normalized_percentile":{"value":0.97281725,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"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":1.0,"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":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9948999881744385,"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":0.8023605346679688},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7313984036445618},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7224032878875732},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6566808223724365},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6218661069869995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6212182641029358},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.617775022983551},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5955485701560974},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4965723156929016},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.48706939816474915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47981762886047363},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4718587100505829},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.42554858326911926},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.42071977257728577},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41333192586898804},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3609423041343689},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07323861122131348},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06554687023162842},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0649285614490509},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06078153848648071}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8023605346679688},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7313984036445618},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7224032878875732},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6566808223724365},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6218661069869995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6212182641029358},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.617775022983551},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5955485701560974},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4965723156929016},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48706939816474915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47981762886047363},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4718587100505829},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.42554858326911926},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.42071977257728577},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41333192586898804},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3609423041343689},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07323861122131348},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06554687023162842},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0649285614490509},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06078153848648071},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p18-1235","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1235","pdf_url":"https://www.aclweb.org/anthology/P18-1235.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-1235","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1235","pdf_url":"https://www.aclweb.org/anthology/P18-1235.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5524522455","display_name":null,"funder_award_id":"DARPA","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G5714049126","display_name":null,"funder_award_id":"911NF-17-C-0098","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G6040357058","display_name":null,"funder_award_id":"W911NF-17-C-0098","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8998121839","display_name":null,"funder_award_id":"911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2798717312.pdf","grobid_xml":"https://content.openalex.org/works/W2798717312.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W193524605","https://openalex.org/W1522301498","https://openalex.org/W1614298861","https://openalex.org/W1793121960","https://openalex.org/W1832693441","https://openalex.org/W2099813784","https://openalex.org/W2112422413","https://openalex.org/W2113459411","https://openalex.org/W2120615054","https://openalex.org/W2131494463","https://openalex.org/W2133564696","https://openalex.org/W2136891251","https://openalex.org/W2144012961","https://openalex.org/W2160660844","https://openalex.org/W2163302275","https://openalex.org/W2250539671","https://openalex.org/W2250851590","https://openalex.org/W2250879510","https://openalex.org/W2251294039","https://openalex.org/W2251939518","https://openalex.org/W2252215182","https://openalex.org/W2311110368","https://openalex.org/W2465978385","https://openalex.org/W2470673105","https://openalex.org/W2493916176","https://openalex.org/W2563010554","https://openalex.org/W2586850891","https://openalex.org/W2612746495","https://openalex.org/W2622365670","https://openalex.org/W2736296425","https://openalex.org/W2787560479","https://openalex.org/W2788625861","https://openalex.org/W2951008357","https://openalex.org/W2951727499","https://openalex.org/W2962739339","https://openalex.org/W2963083845","https://openalex.org/W2963355447","https://openalex.org/W2963687836","https://openalex.org/W2963840100","https://openalex.org/W2964091467","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W2964325543","https://openalex.org/W3196701288"],"related_works":["https://openalex.org/W3192840557","https://openalex.org/W3091976719","https://openalex.org/W3018421652","https://openalex.org/W4220996320","https://openalex.org/W4312200629","https://openalex.org/W4285149559","https://openalex.org/W3021430260","https://openalex.org/W4382286161","https://openalex.org/W3192794374","https://openalex.org/W2889705046"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"excel":[4],"at":[5],"sentiment":[6,56],"polarity":[7],"classification,":[8],"but":[9],"tend":[10],"to":[11,32,44,54],"require":[12],"substantial":[13],"amounts":[14],"of":[15,40,84],"training":[16,38,50],"data,":[17,62],"which":[18,63],"moreover":[19],"differs":[20],"quite":[21],"significantly":[22],"between":[23],"domains.":[24],"In":[25],"this":[26],"work,":[27],"we":[28],"present":[29],"an":[30],"approach":[31],"feed":[33],"generic":[34],"cues":[35],"into":[36,67],"the":[37,68],"process":[39],"such":[41],"networks,":[42],"leading":[43],"better":[45],"generalization":[46],"abilities":[47],"given":[48],"limited":[49],"data.":[51],"We":[52,75],"propose":[53],"induce":[55],"embeddings":[57],"via":[58,70],"supervision":[59],"on":[60,81],"extrinsic":[61],"are":[64],"then":[65],"fed":[66],"model":[69],"a":[71,82],"dedicated":[72],"memorybased":[73],"component.":[74],"observe":[76],"significant":[77],"gains":[78],"in":[79,87],"effectiveness":[80],"range":[83],"different":[85,89],"datasets":[86],"seven":[88],"languages.":[90]},"counts_by_year":[{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":12}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}