{"id":"https://openalex.org/W2251739304","doi":"https://doi.org/10.18653/v1/d15-1018","title":"Joint Prediction for Entity/Event-Level Sentiment Analysis using Probabilistic Soft Logic Models","display_name":"Joint Prediction for Entity/Event-Level Sentiment Analysis using Probabilistic Soft Logic Models","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2251739304","doi":"https://doi.org/10.18653/v1/d15-1018","mag":"2251739304"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d15-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1018","pdf_url":"https://www.aclweb.org/anthology/D15-1018.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D15-1018.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078263110","display_name":"Lingjia Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]},{"id":"https://openalex.org/I4210105785","display_name":"Intelligent Systems Research (United States)","ror":"https://ror.org/01reevc91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210105785"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingjia Deng","raw_affiliation_strings":["Intelligent Systems Program University of Pittsburgh"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Program University of Pittsburgh","institution_ids":["https://openalex.org/I4210105785","https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103355620","display_name":"Janyce Wiebe","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]},{"id":"https://openalex.org/I4210105785","display_name":"Intelligent Systems Research (United States)","ror":"https://ror.org/01reevc91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210105785"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Janyce Wiebe","raw_affiliation_strings":["Intelligent Systems Program Department of Computer Science University of Pittsburgh"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Program Department of Computer Science University of Pittsburgh","institution_ids":["https://openalex.org/I4210105785","https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103355620"],"corresponding_institution_ids":["https://openalex.org/I170201317","https://openalex.org/I4210105785"],"apc_list":null,"apc_paid":null,"fwci":16.4685,"has_fulltext":true,"cited_by_count":71,"citation_normalized_percentile":{"value":0.9908584,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"179","last_page":"189"},"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":0.9983000159263611,"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"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9979000091552734,"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":0.7833462953567505},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7693436145782471},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7267783880233765},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6830803751945496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5388225317001343},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5375784039497375},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48978209495544434},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4778118431568146},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.43406838178634644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4144912362098694},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40913018584251404},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.33107855916023254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7833462953567505},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7693436145782471},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7267783880233765},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6830803751945496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5388225317001343},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5375784039497375},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48978209495544434},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4778118431568146},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.43406838178634644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4144912362098694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40913018584251404},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33107855916023254},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/d15-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1018","pdf_url":"https://www.aclweb.org/anthology/D15-1018.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.696.6543","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.6543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D15/D15-1018.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/d15-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d15-1018","pdf_url":"https://www.aclweb.org/anthology/D15-1018.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 2015 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2778423969","display_name":null,"funder_award_id":"12475008","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5912301711","display_name":null,"funder_award_id":"#12475008","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2251739304.pdf","grobid_xml":"https://content.openalex.org/works/W2251739304.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W123317058","https://openalex.org/W236776272","https://openalex.org/W848102080","https://openalex.org/W1561023189","https://openalex.org/W1835243625","https://openalex.org/W1942169943","https://openalex.org/W1999180776","https://openalex.org/W2014902591","https://openalex.org/W2084837730","https://openalex.org/W2096765155","https://openalex.org/W2100529970","https://openalex.org/W2105834893","https://openalex.org/W2110234338","https://openalex.org/W2115834228","https://openalex.org/W2119821739","https://openalex.org/W2123442489","https://openalex.org/W2140829805","https://openalex.org/W2147218300","https://openalex.org/W2154524383","https://openalex.org/W2154970197","https://openalex.org/W2158184123","https://openalex.org/W2160660844","https://openalex.org/W2165379166","https://openalex.org/W2250981850","https://openalex.org/W2251648804","https://openalex.org/W2251872787","https://openalex.org/W2251939518","https://openalex.org/W2293502436","https://openalex.org/W2401736393","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2548633793","https://openalex.org/W2163814182"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"build":[4],"an":[5],"entity/event-level":[6,68],"sentiment":[7],"analysis":[8],"system,":[9],"which":[10],"is":[11,58],"able":[12,59],"to":[13,60],"recognize":[14],"and":[15,19,24,41],"infer":[16],"both":[17],"explicit":[18,37],"implicit":[20],"sentiments":[21],"toward":[22],"entities":[23],"events":[25],"in":[26,66],"the":[27,56],"text.":[28],"We":[29],"design":[30],"Probabilistic":[31],"Soft":[32],"Logic":[33],"models":[34],"that":[35,46,55],"integrate":[36],"sentiments,":[38],"inference":[39],"rules,":[40],"+/-effect":[42],"event":[43],"information":[44],"(events":[45],"positively":[47],"or":[48],"negatively":[49],"affect":[50],"entities).":[51],"The":[52],"experiments":[53],"show":[54],"method":[57],"greatly":[61],"improve":[62],"over":[63],"baseline":[64],"accuracies":[65],"recognizing":[67],"sentiments.":[69]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":18},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}