{"id":"https://openalex.org/W2954416637","doi":"https://doi.org/10.18653/v1/s19-2195","title":"GWU NLP at SemEval-2019 Task 7: Hybrid Pipeline for Rumour Veracity and Stance Classification on Social Media","display_name":"GWU NLP at SemEval-2019 Task 7: Hybrid Pipeline for Rumour Veracity and Stance Classification on Social Media","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2954416637","doi":"https://doi.org/10.18653/v1/s19-2195","mag":"2954416637"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s19-2195","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s19-2195","pdf_url":"https://www.aclweb.org/anthology/S19-2195.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 13th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S19-2195.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091271513","display_name":"Sardar Hamidian","orcid":"https://orcid.org/0000-0003-1126-7125"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sardar Hamidian","raw_affiliation_strings":["Department of Computer Science The George Washington University Washington DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science The George Washington University Washington DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038581447","display_name":"Mona Diab","orcid":"https://orcid.org/0000-0002-7696-1436"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mona Diab","raw_affiliation_strings":["Department of Computer Science The George Washington University Washington DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science The George Washington University Washington DC, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1115","last_page":"1119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9864000082015991,"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":0.9771000146865845,"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/rumor","display_name":"Rumor","score":0.762200653553009},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7580844759941101},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7183403372764587},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7176795601844788},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.6602784395217896},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6493104696273804},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.6033967733383179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5744943022727966},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5218740701675415},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4845942258834839},{"id":"https://openalex.org/keywords/harm","display_name":"Harm","score":0.47064465284347534},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33907151222229004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.336886465549469},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.30188775062561035},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1443559229373932}],"concepts":[{"id":"https://openalex.org/C2780469804","wikidata":"https://www.wikidata.org/wiki/Q878352","display_name":"Rumor","level":2,"score":0.762200653553009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7580844759941101},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7183403372764587},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7176795601844788},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.6602784395217896},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6493104696273804},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.6033967733383179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5744943022727966},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5218740701675415},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4845942258834839},{"id":"https://openalex.org/C2777363581","wikidata":"https://www.wikidata.org/wiki/Q15098235","display_name":"Harm","level":2,"score":0.47064465284347534},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33907151222229004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.336886465549469},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.30188775062561035},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1443559229373932},{"id":"https://openalex.org/C39549134","wikidata":"https://www.wikidata.org/wiki/Q133080","display_name":"Public relations","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s19-2195","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s19-2195","pdf_url":"https://www.aclweb.org/anthology/S19-2195.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 13th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s19-2195","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s19-2195","pdf_url":"https://www.aclweb.org/anthology/S19-2195.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 13th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2954416637.pdf","grobid_xml":"https://content.openalex.org/works/W2954416637.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1784685665","https://openalex.org/W1971494700","https://openalex.org/W2250539671","https://openalex.org/W2251939518","https://openalex.org/W2726839497","https://openalex.org/W2790166049","https://openalex.org/W2803502351","https://openalex.org/W2913649461","https://openalex.org/W2954444514","https://openalex.org/W2964121744","https://openalex.org/W2996635575","https://openalex.org/W4297730508"],"related_works":["https://openalex.org/W2372853429","https://openalex.org/W2793319716","https://openalex.org/W3110636174","https://openalex.org/W4210503589","https://openalex.org/W2908713064","https://openalex.org/W2810386322","https://openalex.org/W2801267666","https://openalex.org/W2188429085","https://openalex.org/W2886888575","https://openalex.org/W3140274682"],"abstract_inverted_index":{"Social":[0],"media":[1,21],"plays":[2],"a":[3,50,68],"crucial":[4],"role":[5],"as":[6],"the":[7,16,25,40,47,80,83],"main":[8],"resource":[9],"news":[10],"for":[11,44,55],"information":[12],"seekers":[13],"online.":[14],"However,":[15],"unmoderated":[17],"feature":[18],"of":[19,29,39,49,75,82,110],"social":[20],"platforms":[22],"lead":[23],"to":[24,78],"emergence":[26],"and":[27,67,98,101],"spread":[28],"untrustworthy":[30],"contents":[31],"which":[32,72],"harm":[33],"individuals":[34],"or":[35],"even":[36],"societies.":[37],"Most":[38],"current":[41],"automated":[42],"approaches":[43],"automatically":[45],"determining":[46],"veracity":[48,81],"rumor":[51,105],"are":[52],"not":[53],"generalizable":[54],"novel":[56],"emerging":[57],"topics.":[58],"This":[59],"paper":[60,91],"describes":[61],"our":[62],"hybrid":[63],"system":[64,88],"comprising":[65],"rules":[66],"machine":[69],"learning":[70],"model":[71],"makes":[73],"use":[74],"replied":[76],"tweets":[77],"identify":[79],"source":[84],"tweet.":[85],"The":[86],"proposed":[87],"in":[89,95,104,108],"this":[90],"achieved":[92],"0.435":[93],"F-Macro":[94],"stance":[96],"classification,":[97],"0.262":[99],"F-macro":[100],"0.801":[102],"RMSE":[103],"verification":[106],"tasks":[107],"Task7":[109],"Se-mEval":[111],"2019.":[112]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
