{"id":"https://openalex.org/W4388937331","doi":"https://doi.org/10.1109/icccnt56998.2023.10308281","title":"Towards Automated Claim Detection In Fact Checking","display_name":"Towards Automated Claim Detection In Fact Checking","publication_year":2023,"publication_date":"2023-07-06","ids":{"openalex":"https://openalex.org/W4388937331","doi":"https://doi.org/10.1109/icccnt56998.2023.10308281"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt56998.2023.10308281","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10308281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077829910","display_name":"Shristi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shristi","raw_affiliation_strings":["IGDTUW,Dept. of Information Technology,New Delhi,India","Dept. of Information Technology, IGDTUW, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IGDTUW,Dept. of Information Technology,New Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Dept. of Information Technology, IGDTUW, New Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032827950","display_name":"Tanmeet Kaur","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanmeet Kaur","raw_affiliation_strings":["IGDTUW,Dept. of Information Technology,New Delhi,India","Dept. of Information Technology, IGDTUW, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IGDTUW,Dept. of Information Technology,New Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Dept. of Information Technology, IGDTUW, New Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076122501","display_name":"Akanksha Verma","orcid":"https://orcid.org/0000-0001-6121-801X"},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Akanksha Verma","raw_affiliation_strings":["IGDTUW,Dept. of Information Technology,New Delhi,India","Dept. of Information Technology, IGDTUW, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IGDTUW,Dept. of Information Technology,New Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Dept. of Information Technology, IGDTUW, New Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051458180","display_name":"Rishabh Kaushal","orcid":"https://orcid.org/0000-0002-9200-7802"},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rishabh Kaushal","raw_affiliation_strings":["IGDTUW,Dept. of Information Technology,New Delhi,India","Dept. of Information Technology, IGDTUW, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IGDTUW,Dept. of Information Technology,New Delhi,India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Dept. of Information Technology, IGDTUW, New Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27399439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9998999834060669,"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":0.9998999834060669,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9988999962806702,"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/support-vector-machine","display_name":"Support vector machine","score":0.8384643197059631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.770891010761261},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7114138603210449},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6378969550132751},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.626741886138916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6057509779930115},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5668408274650574},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5618264675140381},{"id":"https://openalex.org/keywords/tf\u2013idf","display_name":"tf\u2013idf","score":0.4946992099285126},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4259204864501953},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.42444878816604614},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34819847345352173},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3402850031852722}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8384643197059631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.770891010761261},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7114138603210449},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6378969550132751},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.626741886138916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6057509779930115},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5668408274650574},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5618264675140381},{"id":"https://openalex.org/C81758059","wikidata":"https://www.wikidata.org/wiki/Q796584","display_name":"tf\u2013idf","level":3,"score":0.4946992099285126},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4259204864501953},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.42444878816604614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34819847345352173},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3402850031852722},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt56998.2023.10308281","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt56998.2023.10308281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2011064195","https://openalex.org/W2266769560","https://openalex.org/W2524497217","https://openalex.org/W2743800013","https://openalex.org/W2756923334","https://openalex.org/W2767341768","https://openalex.org/W3035658430","https://openalex.org/W3093767665","https://openalex.org/W3108011434","https://openalex.org/W3152858897","https://openalex.org/W3208070393","https://openalex.org/W3210269434","https://openalex.org/W4287711375","https://openalex.org/W4312494946","https://openalex.org/W6691784016","https://openalex.org/W6693701292","https://openalex.org/W6781407837"],"related_works":["https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4224922629","https://openalex.org/W4385770464","https://openalex.org/W4224262160","https://openalex.org/W3120363735","https://openalex.org/W2394323384","https://openalex.org/W2324052717"],"abstract_inverted_index":{"The":[0],"spread":[1],"of":[2,58,71,106,117,132],"fake":[3,13],"news":[4,14,35],"has":[5],"an":[6],"adverse":[7],"effect":[8],"on":[9,43,127,143],"the":[10,19,44,108,115,149,156],"audience":[11],"as":[12,66,68],"can":[15],"influence":[16],"people":[17],"to":[18,27,32,46,80,101,152],"extent":[20],"that":[21,154],"it":[22,49],"may":[23],"become":[24],"a":[25,34,39,56,72],"threat":[26],"their":[28],"own":[29],"life.":[30],"Therefore,":[31],"verify":[33],"article,":[36],"we":[37,54],"perform":[38],"claim":[40],"detection":[41],"task":[42],"article":[45],"identify":[47],"what":[48],"claims.":[50],"In":[51],"this":[52],"work,":[53],"curate":[55],"dataset":[57,129,158],"183":[59],"fact":[60],"checked":[61],"articles":[62],"from":[63],"India":[64],"Today":[65],"well":[67],"make":[69],"use":[70,77],"benchmark":[73],"dataset,":[74,145],"FactDrill.":[75],"We":[76],"both":[78],"datasets":[79],"train":[81],"model":[82,160],"using":[83,164],"conventional":[84,165],"techniques":[85],"namely":[86],"Decision":[87],"Tree(DTree),":[88],"Naive":[89],"Bayes(NB)":[90],"and":[91,104,119,123,130,134,139,162],"Support":[92,109],"Vector":[93,110],"Machine(SVM)":[94,111],"with":[95,114],"term":[96],"frequency-inverse":[97],"document":[98],"frequency":[99],"approach":[100],"extract":[102],"features":[103],"out":[105],"which":[107],"classifier":[112],"outperforms":[113],"F1-Score":[116,131],"0.40":[118],"0.87":[120],"for":[121,136,159],"Claim":[122,125,137,141],"Not":[124,140],"category":[126,138,142],"our":[128],"0.73":[133],"0.72":[135],"FactDrill":[144,157],"respectively.":[146],"This":[147],"is":[148],"first":[150],"study":[151],"date":[153],"employs":[155],"training":[161],"testing":[163],"methods.":[166]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}