{"id":"https://openalex.org/W2899941041","doi":"https://doi.org/10.3233/web-180389","title":"Transferring sentiment knowledge between words and tweets","display_name":"Transferring sentiment knowledge between words and tweets","publication_year":2018,"publication_date":"2018-10-31","ids":{"openalex":"https://openalex.org/W2899941041","doi":"https://doi.org/10.3233/web-180389","mag":"2899941041"},"language":"en","primary_location":{"id":"doi:10.3233/web-180389","is_oa":false,"landing_page_url":"https://doi.org/10.3233/web-180389","pdf_url":null,"source":{"id":"https://openalex.org/S4210183871","display_name":"Web Intelligence","issn_l":"2405-6456","issn":["2405-6456","2405-6464"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Web Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchcommons.waikato.ac.nz/bitstreams/b7e0ad8d-8412-488a-9dd5-6e27be07104d/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047767877","display_name":"Felipe Bravo-M\u00e1rquez","orcid":"https://orcid.org/0000-0002-2153-4306"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Felipe Bravo-Marquez","raw_affiliation_strings":["Department of Computer Science, University of Waikato, Hamilton, New Zealand. E-mails:\u00a0fbravoma@waikato.ac.nz,\u00a0eibe@waikato.ac.nz,\u00a0bernhard@waikato.ac.nz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Waikato, Hamilton, New Zealand. E-mails:\u00a0fbravoma@waikato.ac.nz,\u00a0eibe@waikato.ac.nz,\u00a0bernhard@waikato.ac.nz","institution_ids":["https://openalex.org/I52179390"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059992863","display_name":"Eibe Frank","orcid":"https://orcid.org/0000-0001-6152-7111"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Eibe Frank","raw_affiliation_strings":["Department of Computer Science, University of Waikato, Hamilton, New Zealand. E-mails:\u00a0fbravoma@waikato.ac.nz,\u00a0eibe@waikato.ac.nz,\u00a0bernhard@waikato.ac.nz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Waikato, Hamilton, New Zealand. E-mails:\u00a0fbravoma@waikato.ac.nz,\u00a0eibe@waikato.ac.nz,\u00a0bernhard@waikato.ac.nz","institution_ids":["https://openalex.org/I52179390"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087785022","display_name":"Bernhard Pfahringer","orcid":"https://orcid.org/0000-0002-3732-5787"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Bernhard Pfahringer","raw_affiliation_strings":["Department of Computer Science, University of Waikato, Hamilton, New Zealand. E-mails:\u00a0fbravoma@waikato.ac.nz,\u00a0eibe@waikato.ac.nz,\u00a0bernhard@waikato.ac.nz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Waikato, Hamilton, New Zealand. E-mails:\u00a0fbravoma@waikato.ac.nz,\u00a0eibe@waikato.ac.nz,\u00a0bernhard@waikato.ac.nz","institution_ids":["https://openalex.org/I52179390"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5047767877"],"corresponding_institution_ids":["https://openalex.org/I52179390"],"apc_list":null,"apc_paid":null,"fwci":0.7378,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80179406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"16","issue":"4","first_page":"203","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9983000159263611,"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":0.7953097820281982},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7028707265853882},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6763293743133545},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6641132831573486},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.617368221282959},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.5916527509689331},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5225198268890381},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5042859315872192},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4853002429008484},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4549618661403656},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4277960956096649},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.36998552083969116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1304541826248169}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7953097820281982},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7028707265853882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6763293743133545},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6641132831573486},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.617368221282959},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.5916527509689331},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5225198268890381},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5042859315872192},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4853002429008484},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4549618661403656},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4277960956096649},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.36998552083969116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1304541826248169},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/web-180389","is_oa":false,"landing_page_url":"https://doi.org/10.3233/web-180389","pdf_url":null,"source":{"id":"https://openalex.org/S4210183871","display_name":"Web Intelligence","issn_l":"2405-6456","issn":["2405-6456","2405-6464"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Web Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:researchcommons.waikato.ac.nz:10289/12209","is_oa":true,"landing_page_url":"https://hdl.handle.net/10289/12209","pdf_url":"https://researchcommons.waikato.ac.nz/bitstreams/b7e0ad8d-8412-488a-9dd5-6e27be07104d/download","source":{"id":"https://openalex.org/S4306400944","display_name":"Research Commons (University of Waikato)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I52179390","host_organization_name":"University of Waikato","host_organization_lineage":["https://openalex.org/I52179390"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:researchcommons.waikato.ac.nz:10289/12209","is_oa":true,"landing_page_url":"https://hdl.handle.net/10289/12209","pdf_url":"https://researchcommons.waikato.ac.nz/bitstreams/b7e0ad8d-8412-488a-9dd5-6e27be07104d/download","source":{"id":"https://openalex.org/S4306400944","display_name":"Research Commons (University of Waikato)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I52179390","host_organization_name":"University of Waikato","host_organization_lineage":["https://openalex.org/I52179390"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311746","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2899941041.pdf","grobid_xml":"https://content.openalex.org/works/W2899941041.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W40549020","https://openalex.org/W152565956","https://openalex.org/W1589554437","https://openalex.org/W1662133657","https://openalex.org/W1800296434","https://openalex.org/W1816079941","https://openalex.org/W1963619433","https://openalex.org/W1994645462","https://openalex.org/W1998257453","https://openalex.org/W2049434052","https://openalex.org/W2064675550","https://openalex.org/W2066551267","https://openalex.org/W2097521684","https://openalex.org/W2101461018","https://openalex.org/W2102419107","https://openalex.org/W2112422413","https://openalex.org/W2121227244","https://openalex.org/W2129011250","https://openalex.org/W2131744502","https://openalex.org/W2143184868","https://openalex.org/W2144378002","https://openalex.org/W2153579005","https://openalex.org/W2154436402","https://openalex.org/W2155328222","https://openalex.org/W2156413587","https://openalex.org/W2157762168","https://openalex.org/W2158139315","https://openalex.org/W2160660844","https://openalex.org/W2161228561","https://openalex.org/W2165612380","https://openalex.org/W2165698076","https://openalex.org/W2199612470","https://openalex.org/W2221308652","https://openalex.org/W2250427924","https://openalex.org/W2250539671","https://openalex.org/W2250966211","https://openalex.org/W2251770468","https://openalex.org/W2251939518","https://openalex.org/W2460474657","https://openalex.org/W2462697095","https://openalex.org/W2558388832","https://openalex.org/W2740582239","https://openalex.org/W2882319491","https://openalex.org/W2950974174","https://openalex.org/W2953061907","https://openalex.org/W3106003309","https://openalex.org/W3146306708","https://openalex.org/W4252793191","https://openalex.org/W6604896550","https://openalex.org/W6611801733","https://openalex.org/W6629159331","https://openalex.org/W6678277124","https://openalex.org/W6812014127","https://openalex.org/W6813344030"],"related_works":["https://openalex.org/W2888662092","https://openalex.org/W3205826705","https://openalex.org/W2903394456","https://openalex.org/W2902285665","https://openalex.org/W3119550360","https://openalex.org/W2593058442","https://openalex.org/W1631585051","https://openalex.org/W2975174210","https://openalex.org/W2150818832","https://openalex.org/W4200238620"],"abstract_inverted_index":{"Message-level":[0],"and":[1,71,106,119,135,148,151,164,171,239,263],"word-level":[2,236],"polarity":[3,244,250],"classification":[4,230],"are":[5,97,108],"two":[6,85,129,224],"popular":[7],"tasks":[8],"in":[9,115,160,193,223],"Twitter":[10],"sentiment":[11,61,200,229,237],"analysis.":[12],"They":[13],"have":[14],"been":[15],"commonly":[16],"addressed":[17],"by":[18,74,122,141,153,233,246],"training":[19],"supervised":[20],"models":[21,30],"from":[22,41,63,92,206,215],"labelled":[23,204],"data.":[24],"The":[25],"main":[26],"limitation":[27],"of":[28,35,83,90,101,112,157,178,183,189,231,242],"these":[29,84],"is":[31,46,186],"the":[32,64,68,88,93,102,113,124,155,158,174,194,216,256],"high":[33],"cost":[34],"data":[36,205],"annotation.":[37],"Transferring":[38],"existing":[39],"labels":[40,62],"a":[42,199,235,243,248],"related":[43],"problem":[44],"domain":[45,66,70,208],"one":[47,207],"possible":[48],"solution":[49],"for":[50,132],"this":[51,54,221],"problem.":[52],"In":[53],"paper,":[55],"we":[56],"study":[57,128],"how":[58],"to":[59,67,212],"transfer":[60,225],"word":[65,136],"tweet":[69,134],"vice":[72],"versa":[73],"making":[75],"their":[76,179],"corresponding":[77,125],"instances":[78,82,91,188,214],"compatible.":[79],"We":[80,127,219],"model":[81,258],"domains":[86,191],"as":[87,99,110,146,173],"aggregation":[89,121],"other":[94,217],"(i.e.,":[95],"tweets":[96,114,140,159,172,232,264],"treated":[98,109],"collections":[100,111],"words":[103,107,152,167,262],"they":[104,117,162],"contain":[105],"which":[116,161],"occur)":[118],"perform":[120],"averaging":[123,133,154],"constituents.":[126],"different":[130],"setups":[131],"vectors:":[137],"1)":[138,228],"representing":[139,166],"standard":[142],"NLP":[143],"features":[144],"such":[145],"unigrams":[147],"part-of-speech":[149],"tags":[150],"vectors":[156],"occur,":[163],"2)":[165,240],"using":[168],"skip-gram":[169],"embeddings":[170],"average":[175],"embedding":[176],"vector":[177],"words.":[180],"A":[181],"consequence":[182],"our":[184],"approach":[185,222],"that":[187,255],"both":[190],"reside":[192],"same":[195],"feature":[196],"space.":[197],"Thus,":[198],"classifier":[201],"trained":[202],"on":[203],"can":[209,259],"be":[210],"used":[211],"classify":[213,261],"one.":[218],"evaluate":[220],"learning":[226],"tasks:":[227],"applying":[234,247],"classifier,":[238],"induction":[241],"lexicon":[245],"tweet-level":[249],"classifier.":[251],"Our":[252],"results":[253],"show":[254],"proposed":[257],"successfully":[260],"after":[265],"transfer.":[266]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}