{"id":"https://openalex.org/W3108108409","doi":"https://doi.org/10.1108/el-05-2020-0120","title":"Spam detection and high-quality features to analyse question \u2013answer pairs","display_name":"Spam detection and high-quality features to analyse question \u2013answer pairs","publication_year":2020,"publication_date":"2020-11-25","ids":{"openalex":"https://openalex.org/W3108108409","doi":"https://doi.org/10.1108/el-05-2020-0120","mag":"3108108409"},"language":"en","primary_location":{"id":"doi:10.1108/el-05-2020-0120","is_oa":false,"landing_page_url":"https://doi.org/10.1108/el-05-2020-0120","pdf_url":null,"source":{"id":"https://openalex.org/S902750600","display_name":"The Electronic Library","issn_l":"0264-0473","issn":["0264-0473","1758-616X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Electronic Library","raw_type":"journal-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/A5035284205","display_name":"Hei\u2010Chia Wang","orcid":"https://orcid.org/0000-0002-5790-7506"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hei Chia Wang","raw_affiliation_strings":["Department of Industrial and Information Management, Institute of Information Management, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Information Management, Institute of Information Management, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033603058","display_name":"Yu Hung Chiang","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu Hung Chiang","raw_affiliation_strings":["Department of Industrial and Information Management, Institute of Information Management, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Information Management, Institute of Information Management, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062156743","display_name":"Si Ting Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Si Ting Lin","raw_affiliation_strings":["Department of Industrial and Information Management, Institute of Information Management, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Information Management, Institute of Information Management, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035284205"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":null,"apc_paid":null,"fwci":0.8354,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8197946,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"38","issue":"5/6","first_page":"1013","last_page":"1033"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9998999834060669,"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":0.9986000061035156,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7501087784767151},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6579886078834534},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6203559637069702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.608838677406311},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5688228607177734},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5391526222229004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5389782190322876},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49606284499168396},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.482172429561615},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4503445029258728},{"id":"https://openalex.org/keywords/questions-and-answers","display_name":"Questions and answers","score":0.43635204434394836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7501087784767151},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6579886078834534},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6203559637069702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.608838677406311},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5688228607177734},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5391526222229004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5389782190322876},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49606284499168396},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.482172429561615},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4503445029258728},{"id":"https://openalex.org/C3019144022","wikidata":"https://www.wikidata.org/wiki/Q4124998","display_name":"Questions and answers","level":2,"score":0.43635204434394836},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/el-05-2020-0120","is_oa":false,"landing_page_url":"https://doi.org/10.1108/el-05-2020-0120","pdf_url":null,"source":{"id":"https://openalex.org/S902750600","display_name":"The Electronic Library","issn_l":"0264-0473","issn":["0264-0473","1758-616X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Electronic Library","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W9224363","https://openalex.org/W1481786127","https://openalex.org/W1961365048","https://openalex.org/W1965370992","https://openalex.org/W1972395148","https://openalex.org/W1977764012","https://openalex.org/W1978317631","https://openalex.org/W1990457736","https://openalex.org/W2005946396","https://openalex.org/W2012378416","https://openalex.org/W2031540871","https://openalex.org/W2037858832","https://openalex.org/W2055753488","https://openalex.org/W2056030284","https://openalex.org/W2057415299","https://openalex.org/W2062628331","https://openalex.org/W2099592858","https://openalex.org/W2114732275","https://openalex.org/W2120215850","https://openalex.org/W2143337100","https://openalex.org/W2148118556","https://openalex.org/W2155712036","https://openalex.org/W2158894970","https://openalex.org/W2165201985","https://openalex.org/W2192783609","https://openalex.org/W2212434113","https://openalex.org/W2233955765","https://openalex.org/W2276398615","https://openalex.org/W2294062734","https://openalex.org/W2296283641","https://openalex.org/W2346875348","https://openalex.org/W2364207564","https://openalex.org/W2418912424","https://openalex.org/W2514077680","https://openalex.org/W2604518650","https://openalex.org/W2605443677","https://openalex.org/W2608384516","https://openalex.org/W2724565823","https://openalex.org/W2767877950","https://openalex.org/W2771926299","https://openalex.org/W2773166092","https://openalex.org/W2808354323","https://openalex.org/W2913146023","https://openalex.org/W2914966672","https://openalex.org/W2919057541","https://openalex.org/W3002078994","https://openalex.org/W3048149209","https://openalex.org/W3179783984","https://openalex.org/W4243989635"],"related_works":["https://openalex.org/W2118632115","https://openalex.org/W2555213299","https://openalex.org/W2576107865","https://openalex.org/W3215363805","https://openalex.org/W1846393350","https://openalex.org/W3154330131","https://openalex.org/W4307481286","https://openalex.org/W4226441484","https://openalex.org/W2577658701","https://openalex.org/W4245428286"],"abstract_inverted_index":{"Purpose":[0],"In":[1],"community":[2],"question":[3,77,202,225],"and":[4,12,48,69,78,120,242,266,271],"answer":[5,20,45,50,79,93,147,175,197,240,248,303],"(CQA)":[6],"services,":[7],"because":[8],"of":[9,15,19,37,55,76,92,99,136,157,182,253,281,298,317,322],"user":[10],"subjectivity":[11],"the":[13,17,53,73,180,215,218,224,231,295,320],"limits":[14],"knowledge,":[16],"distribution":[18],"quality":[21,46,94,148,176,198,249],"can":[22,178,301,328],"vary":[23],"drastically":[24],"\u2013":[25],"from":[26,319],"highly":[27],"related":[28],"to":[29,59,131,144,154,262,278],"irrelevant":[30],"or":[31],"even":[32],"spam":[33,49,61,116,171,189,264],"answers.":[34,190],"Previous":[35],"studies":[36],"CQA":[38],"portals":[39],"have":[40],"faced":[41],"two":[42],"important":[43],"issues:":[44],"analysis":[47,177,208],"filtering.":[51],"Therefore,":[52],"purposes":[54],"this":[56,86,286],"study":[57,87,91,104,167,287],"are":[58,161,186,204],"filter":[60],"answers":[62,117,153,184,265,277,312,324],"in":[63,118,223,283,325,332],"advance":[64,119],"using":[65],"two-phase":[66,111],"identification":[67,112,307],"methods":[68],"then":[70],"automatically":[71,132,309],"classify":[72,133],"different":[74,97,155,211,251,279,296,315],"types":[75,98,135,156,203,252,280,297],"(QA)":[80],"pairs":[81],"by":[82,234],"deep":[83,123],"learning.":[84],"Finally,":[85,230],"proposes":[88,105],"a":[89,110,122],"comprehensive":[90],"prediction":[95],"for":[96,210,250,275,313],"QA":[100],"pairs.":[101],"Design/methodology/approach":[102],"This":[103,166],"an":[106,174,306],"integrated":[107],"model":[108],"with":[109,269],"method":[113,125],"that":[114,169,185,196,214,237,290,300],"filters":[115],"uses":[121],"learning":[124],"[recurrent":[126],"convolutional":[127],"neural":[128],"network":[129],"(R-CNN)]":[130],"various":[134],"questions.":[137,158,254],"Logistic":[138],"regression":[139],"(LR)":[140],"is":[141,199,259],"further":[142,288],"applied":[143],"examine":[145],"which":[146,327],"features":[149,292],"significantly":[150,246],"indicate":[151],"high-quality":[152,183,276,311],"Findings":[159],"There":[160],"four":[162],"prominent":[163],"findings.":[164],"(1)":[165],"confirms":[168],"conducting":[170],"filtering":[172],"before":[173],"reduce":[179],"proportion":[181],"misjudged":[187],"as":[188],"(2)":[191],"The":[192,207,256],"experimental":[193,232],"results":[194,209,233],"show":[195,213,236],"better":[200],"when":[201],"included.":[205],"(3)":[206],"classifiers":[212],"R-CNN":[216],"achieves":[217],"best":[219],"macro-F1":[220],"scores":[221],"(74.8%)":[222],"type":[226,316],"classification":[227],"module.":[228],"(4)":[229],"LR":[235],"author":[238],"ranking,":[239],"length":[241],"common":[243],"words":[244],"could":[245],"impact":[247,302],"Originality/value":[255],"proposed":[257],"system":[258,308],"simultaneously":[260],"able":[261],"detect":[263],"provide":[267],"users":[268,334],"quick":[270],"efficient":[272],"retrieval":[273],"mechanisms":[274],"questions":[282,299,318],"CQA.":[284],"Moreover,":[285],"validates":[289],"crucial":[291],"exist":[293],"among":[294],"quality.":[304],"Overall,":[305],"summarises":[310],"each":[314],"pool":[321],"messy":[323],"CQA,":[326],"be":[329],"very":[330],"useful":[331],"helping":[333],"make":[335],"decisions.":[336]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}