{"id":"https://openalex.org/W4412777105","doi":"https://doi.org/10.1145/3757747","title":"From Stars to Insights: Exploration and Implementation of Unified Sentiment Analysis with Distant Supervision","display_name":"From Stars to Insights: Exploration and Implementation of Unified Sentiment Analysis with Distant Supervision","publication_year":2025,"publication_date":"2025-07-31","ids":{"openalex":"https://openalex.org/W4412777105","doi":"https://doi.org/10.1145/3757747"},"language":"en","primary_location":{"id":"doi:10.1145/3757747","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757747","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3757747","source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3757747","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101998578","display_name":"Wenchang Li","orcid":"https://orcid.org/0000-0001-9323-2932"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenchang Li","raw_affiliation_strings":["Department of Information Management, Peking University","Department of Information Management, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9323-2932","affiliations":[{"raw_affiliation_string":"Department of Information Management, Peking University","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Department of Information Management, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033125725","display_name":"John P. Lalor","orcid":"https://orcid.org/0000-0003-0848-4786"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John P. Lalor","raw_affiliation_strings":["Mendoza College of Business, University of Notre Dame","Mendoza College of Business, University of Notre Dame, Notre Dame, United States"],"raw_orcid":"https://orcid.org/0000-0003-0848-4786","affiliations":[{"raw_affiliation_string":"Mendoza College of Business, University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"Mendoza College of Business, University of Notre Dame, Notre Dame, United States","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101850830","display_name":"Yixing Chen","orcid":"https://orcid.org/0000-0001-5509-4161"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yixing Chen","raw_affiliation_strings":["Mendoza College of Business, University of Notre Dame","Mendoza College of Business, University of Notre Dame, Notre Dame, United States"],"raw_orcid":"https://orcid.org/0000-0001-5509-4161","affiliations":[{"raw_affiliation_string":"Mendoza College of Business, University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"Mendoza College of Business, University of Notre Dame, Notre Dame, United States","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009048860","display_name":"Vamsi K. Kanuri","orcid":"https://orcid.org/0000-0002-6228-8017"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vamsi K. Kanuri","raw_affiliation_strings":["Mendoza College of Business, University of Notre Dame","Mendoza College of Business, University of Notre Dame, Notre Dame, United States"],"raw_orcid":"https://orcid.org/0000-0002-6228-8017","affiliations":[{"raw_affiliation_string":"Mendoza College of Business, University of Notre Dame","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"Mendoza College of Business, University of Notre Dame, Notre Dame, United States","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07068438,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"3","first_page":"1","last_page":"21"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9962999820709229,"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":0.9872000217437744,"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/stars","display_name":"Stars","score":0.6918361783027649},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.44793426990509033},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3752864897251129},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3526111841201782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19744715094566345},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.05321460962295532}],"concepts":[{"id":"https://openalex.org/C150846664","wikidata":"https://www.wikidata.org/wiki/Q7602306","display_name":"Stars","level":2,"score":0.6918361783027649},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.44793426990509033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3752864897251129},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3526111841201782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19744715094566345},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.05321460962295532}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3757747","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757747","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3757747","source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3757747","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757747","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3757747","source":{"id":"https://openalex.org/S4210170305","display_name":"ACM Transactions on Management Information Systems","issn_l":"2158-656X","issn":["2158-656X","2158-6578"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Management Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412777105.pdf","grobid_xml":"https://content.openalex.org/works/W4412777105.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W66373487","https://openalex.org/W1554540371","https://openalex.org/W1602136775","https://openalex.org/W2251648804","https://openalex.org/W2253519362","https://openalex.org/W2489487449","https://openalex.org/W2599674900","https://openalex.org/W2607303097","https://openalex.org/W2613000335","https://openalex.org/W2623399293","https://openalex.org/W2750779823","https://openalex.org/W2771576526","https://openalex.org/W2774772126","https://openalex.org/W2891434004","https://openalex.org/W2899575547","https://openalex.org/W2963337756","https://openalex.org/W2972850605","https://openalex.org/W2990663995","https://openalex.org/W3128065830","https://openalex.org/W3142952120","https://openalex.org/W4205807230","https://openalex.org/W4224307896","https://openalex.org/W4226322105","https://openalex.org/W4234859835","https://openalex.org/W4239019441","https://openalex.org/W4250331344","https://openalex.org/W4253203888","https://openalex.org/W4282016500","https://openalex.org/W4285392642","https://openalex.org/W4288760206","https://openalex.org/W4298359459","https://openalex.org/W4301101316","https://openalex.org/W4365799947","https://openalex.org/W4391136348","https://openalex.org/W4407564579"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989"],"abstract_inverted_index":{"Sentiment":[0],"analysis":[1,18],"is":[2],"integral":[3],"to":[4,82,122],"understanding":[5],"the":[6,9,58,71,133],"voice":[7],"of":[8,125,135],"customer":[10],"and":[11,28,40,88,102,143],"informing":[12],"businesses\u2019":[13],"strategic":[14],"decisions.":[15],"Conventional":[16],"sentiment":[17,26,50,84,152],"involves":[19],"three":[20,59],"separate":[21],"tasks:":[22],"aspect-category":[23,25],"detection,":[24],"analysis,":[27,51],"rating":[29,110],"prediction.":[30],"However,":[31],"independently":[32],"tackling":[33],"these":[34],"tasks":[35,61],"can":[36],"overlook":[37],"their":[38],"interdependencies":[39],"often":[41],"requires":[42],"expensive,":[43],"fine-grained":[44],"annotations.":[45],"This":[46],"article":[47],"introduces":[48],"unified":[49,149],"a":[52,63,79,92,123,146],"novel":[53],"learning":[54],"paradigm":[55],"that":[56,105],"integrates":[57],"aforementioned":[60],"into":[62],"coherent":[64],"framework.":[65],"To":[66],"achieve":[67],"this,":[68],"we":[69],"propose":[70],"Distantly":[72],"Supervised":[73],"Pyramid":[74],"Network":[75],"(DSPN),":[76],"which":[77],"employs":[78],"pyramid":[80,130],"structure":[81,131],"capture":[83],"at":[85],"word,":[86],"aspect,":[87],"document":[89],"levels":[90],"in":[91,100],"hierarchical":[93],"manner.":[94],"Evaluations":[95],"on":[96],"multi-aspect":[97],"review":[98],"datasets":[99],"English":[101],"Chinese":[103],"show":[104],"DSPN,":[106],"using":[107],"only":[108],"star":[109],"labels":[111],"for":[112,151],"supervision,":[113],"demonstrates":[114],"significant":[115],"efficiency":[116],"advantages":[117],"while":[118],"performing":[119],"comparably":[120],"well":[121],"variety":[124],"benchmark":[126],"models.":[127],"Additionally,":[128],"DSPN\u2019s":[129,141],"enables":[132],"interpretability":[134],"its":[136],"outputs.":[137],"Our":[138],"findings":[139],"validate":[140],"effectiveness":[142],"efficiency,":[144],"establishing":[145],"robust,":[147],"resource-efficient,":[148],"framework":[150],"analysis.":[153]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
