{"id":"https://openalex.org/W3148001275","doi":"https://doi.org/10.1109/tcss.2021.3068519","title":"WELFake: Word Embedding Over Linguistic Features for Fake News Detection","display_name":"WELFake: Word Embedding Over Linguistic Features for Fake News Detection","publication_year":2021,"publication_date":"2021-04-05","ids":{"openalex":"https://openalex.org/W3148001275","doi":"https://doi.org/10.1109/tcss.2021.3068519","mag":"3148001275"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2021.3068519","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tcss.2021.3068519","pdf_url":"https://ieeexplore.ieee.org/ielx7/6570650/9502055/09395133.pdf","source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/6570650/9502055/09395133.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047063595","display_name":"Pawan Kumar Verma","orcid":"https://orcid.org/0000-0002-2189-3974"},"institutions":[{"id":"https://openalex.org/I110360157","display_name":"Lovely Professional University","ror":"https://ror.org/00et6q107","country_code":"IN","type":"education","lineage":["https://openalex.org/I110360157"]},{"id":"https://openalex.org/I82571370","display_name":"GLA University","ror":"https://ror.org/05fnxgv12","country_code":"IN","type":"education","lineage":["https://openalex.org/I82571370"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pawan Kumar Verma","raw_affiliation_strings":["GLA University, Mathura, India","School of Computer Science and Engineering, Lovely Professional University, Phagwara, India"],"raw_orcid":"https://orcid.org/0000-0002-2189-3974","affiliations":[{"raw_affiliation_string":"GLA University, Mathura, India","institution_ids":["https://openalex.org/I82571370"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Lovely Professional University, Phagwara, India","institution_ids":["https://openalex.org/I110360157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047443199","display_name":"Prateek Agrawal","orcid":"https://orcid.org/0000-0001-6861-0698"},"institutions":[{"id":"https://openalex.org/I110360157","display_name":"Lovely Professional University","ror":"https://ror.org/00et6q107","country_code":"IN","type":"education","lineage":["https://openalex.org/I110360157"]},{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT","IN"],"is_corresponding":false,"raw_author_name":"Prateek Agrawal","raw_affiliation_strings":["Institute of Information Technology, University of Klagenfurt, Klagenfurt, Austria","School of Computer Science and Engineering, Lovely Professional University, Phagwara, India"],"raw_orcid":"https://orcid.org/0000-0001-6861-0698","affiliations":[{"raw_affiliation_string":"Institute of Information Technology, University of Klagenfurt, Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Lovely Professional University, Phagwara, India","institution_ids":["https://openalex.org/I110360157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006784402","display_name":"Ivone Amorim","orcid":"https://orcid.org/0000-0001-6102-6165"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Ivone Amorim","raw_affiliation_strings":["CMUP Mathematical Research Center, University of Porto, Porto, Portugal","MOG Technologies, Moreira, Portugal"],"raw_orcid":"https://orcid.org/0000-0001-6102-6165","affiliations":[{"raw_affiliation_string":"CMUP Mathematical Research Center, University of Porto, Porto, Portugal","institution_ids":["https://openalex.org/I182534213"]},{"raw_affiliation_string":"MOG Technologies, Moreira, Portugal","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050009901","display_name":"Radu Prodan","orcid":"https://orcid.org/0000-0002-8247-5426"},"institutions":[{"id":"https://openalex.org/I4210166741","display_name":"University of Klagenfurt","ror":"https://ror.org/05q9m0937","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210166741"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Radu Prodan","raw_affiliation_strings":["Institute of Information Technology, University of Klagenfurt, Klagenfurt, Austria"],"raw_orcid":"https://orcid.org/0000-0002-8247-5426","affiliations":[{"raw_affiliation_string":"Institute of Information Technology, University of Klagenfurt, Klagenfurt, Austria","institution_ids":["https://openalex.org/I4210166741"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047063595"],"corresponding_institution_ids":["https://openalex.org/I110360157","https://openalex.org/I82571370"],"apc_list":null,"apc_paid":null,"fwci":68.2256,"has_fulltext":true,"cited_by_count":277,"citation_normalized_percentile":{"value":0.99942688,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"8","issue":"4","first_page":"881","last_page":"893"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":1.0,"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":1.0,"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":0.9979000091552734,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9890999794006348,"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":0.7765341997146606},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6024898886680603},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5933449268341064},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.5739165544509888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5676295757293701},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.49641233682632446},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4958389699459076},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48186883330345154},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.48115527629852295},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.480354905128479},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.47413870692253113},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47372522950172424},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4311245381832123},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4307861030101776},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4168323576450348},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.35957297682762146},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.33873048424720764},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.17340874671936035},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.16682380437850952}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7765341997146606},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6024898886680603},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5933449268341064},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.5739165544509888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5676295757293701},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.49641233682632446},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4958389699459076},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48186883330345154},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.48115527629852295},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.480354905128479},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.47413870692253113},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47372522950172424},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4311245381832123},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4307861030101776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4168323576450348},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.35957297682762146},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33873048424720764},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.17340874671936035},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.16682380437850952},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcss.2021.3068519","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tcss.2021.3068519","pdf_url":"https://ieeexplore.ieee.org/ielx7/6570650/9502055/09395133.pdf","source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},{"id":"pmh:oai:zenodo.org:4692818","is_oa":true,"landing_page_url":"https://doi.org/10.1109/TCSS.2021.3068519","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Computational Social Systems, (2021-04-05)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/tcss.2021.3068519","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tcss.2021.3068519","pdf_url":"https://ieeexplore.ieee.org/ielx7/6570650/9502055/09395133.pdf","source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G6028836076","display_name":null,"funder_award_id":"825134","funder_id":"https://openalex.org/F4320337663","funder_display_name":"H2020 Industrial Leadership"},{"id":"https://openalex.org/G8764417039","display_name":"smART socIal media eCOsytstem in a blockchaiN Federated environment","funder_award_id":"825134","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320337663","display_name":"H2020 Industrial Leadership","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3148001275.pdf","grobid_xml":"https://content.openalex.org/works/W3148001275.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W621249151","https://openalex.org/W1514681859","https://openalex.org/W1576604406","https://openalex.org/W2018093805","https://openalex.org/W2035896792","https://openalex.org/W2084591134","https://openalex.org/W2091034860","https://openalex.org/W2132210327","https://openalex.org/W2133564696","https://openalex.org/W2248267741","https://openalex.org/W2280267672","https://openalex.org/W2509979611","https://openalex.org/W2531862055","https://openalex.org/W2543744876","https://openalex.org/W2582610994","https://openalex.org/W2604264634","https://openalex.org/W2610839185","https://openalex.org/W2690773701","https://openalex.org/W2735017898","https://openalex.org/W2749784378","https://openalex.org/W2757749329","https://openalex.org/W2759820691","https://openalex.org/W2763699126","https://openalex.org/W2770039499","https://openalex.org/W2778250944","https://openalex.org/W2790166049","https://openalex.org/W2894278110","https://openalex.org/W2901048557","https://openalex.org/W2903782735","https://openalex.org/W2912173431","https://openalex.org/W2924988155","https://openalex.org/W2946762810","https://openalex.org/W2947813521","https://openalex.org/W2951307134","https://openalex.org/W2963416784","https://openalex.org/W2963877803","https://openalex.org/W2963968475","https://openalex.org/W2964308564","https://openalex.org/W2978621926","https://openalex.org/W2979572588","https://openalex.org/W2980708516","https://openalex.org/W3001895040","https://openalex.org/W3004824158","https://openalex.org/W3015467872","https://openalex.org/W3099727075","https://openalex.org/W3102739576","https://openalex.org/W3103384135","https://openalex.org/W3109536455","https://openalex.org/W3209629859","https://openalex.org/W4299567010","https://openalex.org/W6619475645","https://openalex.org/W6630762190","https://openalex.org/W6725002042","https://openalex.org/W6739951937","https://openalex.org/W6741252931","https://openalex.org/W6746779577","https://openalex.org/W6763240421","https://openalex.org/W6772995007","https://openalex.org/W6787259092"],"related_works":["https://openalex.org/W2946409105","https://openalex.org/W2985392712","https://openalex.org/W4388996947","https://openalex.org/W3133567596","https://openalex.org/W2798009317","https://openalex.org/W3203949288","https://openalex.org/W4382201653","https://openalex.org/W3175524270","https://openalex.org/W2998070955","https://openalex.org/W2770162183"],"abstract_inverted_index":{"Social":[0],"media":[1,46],"is":[2,21,76],"a":[3,52,93,156,192],"popular":[4],"medium":[5],"for":[6,26,81,107],"the":[7,14,24,57,82,119,124,137,181,185,196,232],"dissemination":[8],"of":[9,23,32,59,84,126],"real-time":[10],"news":[11,109,127,186],"all":[12],"over":[13,104],"world.":[15],"Easy":[16],"and":[17,39,66,122,143,189,209,220],"quick":[18],"information":[19,68],"proliferation":[20],"one":[22],"reasons":[25],"its":[27,72,149],"popularity.":[28],"An":[29],"extensive":[30],"number":[31],"users":[33],"with":[34,141,161,191],"different":[35,168],"age":[36],"groups,":[37],"gender,":[38],"societal":[40],"beliefs":[41],"are":[42],"engaged":[43],"in":[44,56,187],"social":[45],"websites.":[47],"Despite":[48],"these":[49],"favorable":[50],"aspects,":[51],"significant":[53],"disadvantage":[54],"comes":[55],"form":[58],"fake":[60,108,190],"news,":[61],"as":[62],"people":[63],"usually":[64],"read":[65],"share":[67],"without":[69],"caring":[70],"about":[71],"genuineness.":[73],"Therefore,":[74],"it":[75],"imperative":[77],"to":[78,171,202,212,238],"research":[79],"methods":[80],"authentication":[83],"news.":[85],"To":[86,147],"address":[87],"this":[88,90,151],"issue,":[89],"article":[91,152],"proposes":[92],"two-phase":[94],"benchmark":[95],"model":[96,183,225],"named":[97],"WELFake":[98,158,182],"based":[99],"on":[100],"word":[101],"embedding":[102],"(WE)":[103],"linguistic":[105,131,138],"features":[106],"detection":[110],"using":[111,130,231],"machine":[112],"learning":[113],"classification.":[114,146],"The":[115,133],"first":[116],"phase":[117,135],"preprocesses":[118],"data":[120,159,169],"set":[121,160],"validates":[123],"veracity":[125],"content":[128],"by":[129,199,236],"features.":[132],"second":[134],"merges":[136],"feature":[139],"sets":[140,170],"WE":[142,234],"applies":[144],"voting":[145],"validate":[148],"approach,":[150],"also":[153],"carefully":[154],"designs":[155],"novel":[157],"approximately":[162],"72":[163],"000":[164],"articles,":[165],"which":[166,194],"incorporates":[167],"generate":[172],"an":[173],"unbiased":[174],"classification":[175],"output.":[176],"Experimental":[177],"results":[178],"show":[179],"that":[180],"categorizes":[184],"real":[188],"96.73%":[193],"improves":[195],"overall":[197],"accuracy":[198],"1.31%":[200],"compared":[201,211],"bidirectional":[203],"encoder":[204],"representations":[205],"from":[206],"transformer":[207],"(BERT)":[208],"4.25%":[210],"convolutional":[213],"neural":[214],"network":[215],"(CNN)":[216],"models.":[217],"Our":[218],"frequency-based":[219],"focused":[221],"analyzing":[222],"writing":[223],"patterns":[224],"outperforms":[226],"predictive-based":[227],"related":[228],"works":[229],"implemented":[230],"Word2vec":[233],"method":[235],"up":[237],"1.73%.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":81},{"year":2024,"cited_by_count":77},{"year":2023,"cited_by_count":63},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":8}],"updated_date":"2026-05-31T08:46:17.908082","created_date":"2025-10-10T00:00:00"}