{"id":"https://openalex.org/W7167934706","doi":"https://doi.org/10.1515/comp-2025-0061","title":"Algorithm-specific effects of class balancing: statistical evidence from Turkish institutional document classification","display_name":"Algorithm-specific effects of class balancing: statistical evidence from Turkish institutional document classification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7167934706","doi":"https://doi.org/10.1515/comp-2025-0061"},"language":"en","primary_location":{"id":"doi:10.1515/comp-2025-0061","is_oa":true,"landing_page_url":"https://doi.org/10.1515/comp-2025-0061","pdf_url":null,"source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1515/comp-2025-0061","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140384296","display_name":"Ba\u011fda G\u00fcl \u0130l\u00e7i","orcid":null},"institutions":[{"id":"https://openalex.org/I149717392","display_name":"Siirt \u00dcniversitesi","ror":"https://ror.org/05ptwtz25","country_code":"TR","type":"education","lineage":["https://openalex.org/I149717392"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ba\u011fda G\u00fcl \u0130l\u00e7i","raw_affiliation_strings":["Computer Engineering Department , Siirt University , Siirt 56100 , T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Department , Siirt University , Siirt 56100 , T\u00fcrkiye","institution_ids":["https://openalex.org/I149717392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5140389031","display_name":"\u00d6zlem Batur Dinler","orcid":null},"institutions":[{"id":"https://openalex.org/I149717392","display_name":"Siirt \u00dcniversitesi","ror":"https://ror.org/05ptwtz25","country_code":"TR","type":"education","lineage":["https://openalex.org/I149717392"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"\u00d6zlem Batur Dinler","raw_affiliation_strings":["Computer Engineering Department , Siirt University , Siirt 56100 , T\u00fcrkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Department , Siirt University , Siirt 56100 , T\u00fcrkiye","institution_ids":["https://openalex.org/I149717392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149717392"],"apc_list":{"value":1050,"currency":"EUR","value_usd":1187},"apc_paid":{"value":1050,"currency":"EUR","value_usd":1187},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7416947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.781000018119812,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.781000018119812,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.09780000150203705,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.021800000220537186,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/turkish","display_name":"Turkish","score":0.6269999742507935},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6079000234603882},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6075000166893005},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5113999843597412},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4945000112056732},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4763999879360199},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3799000084400177},{"id":"https://openalex.org/keywords/statistical-analysis","display_name":"Statistical analysis","score":0.37619999051094055}],"concepts":[{"id":"https://openalex.org/C2781121862","wikidata":"https://www.wikidata.org/wiki/Q256","display_name":"Turkish","level":2,"score":0.6269999742507935},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6079000234603882},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6075000166893005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5206000208854675},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5113999843597412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5073000192642212},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4945000112056732},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4763999879360199},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.37619999051094055},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36399999260902405},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3061000108718872},{"id":"https://openalex.org/C2993259228","wikidata":"https://www.wikidata.org/wiki/Q3320364","display_name":"Statistical evidence","level":3,"score":0.30000001192092896},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C114928208","wikidata":"https://www.wikidata.org/wiki/Q17104952","display_name":"Pairwise independence","level":5,"score":0.28999999165534973},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2842000126838684},{"id":"https://openalex.org/C44648626","wikidata":"https://www.wikidata.org/wiki/Q1049848","display_name":"Percentage point","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27549999952316284}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1515/comp-2025-0061","is_oa":true,"landing_page_url":"https://doi.org/10.1515/comp-2025-0061","pdf_url":null,"source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:691a72a269c24a05bfe47510144d2422","is_oa":false,"landing_page_url":"https://doaj.org/article/691a72a269c24a05bfe47510144d2422","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Open Computer Science, Vol 16, Iss 1, Pp 321-357 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1515/comp-2025-0061","is_oa":true,"landing_page_url":"https://doi.org/10.1515/comp-2025-0061","pdf_url":null,"source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5393109917640686,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1591261915","https://openalex.org/W1982439145","https://openalex.org/W1993220166","https://openalex.org/W2099454382","https://openalex.org/W2104933073","https://openalex.org/W2118978333","https://openalex.org/W2132791018","https://openalex.org/W2148143831","https://openalex.org/W2164330572","https://openalex.org/W2164777277","https://openalex.org/W2217007515","https://openalex.org/W2338318698","https://openalex.org/W2490420619","https://openalex.org/W2562319768","https://openalex.org/W2604504584","https://openalex.org/W2892131163","https://openalex.org/W2906461268","https://openalex.org/W2945976633","https://openalex.org/W2980708516","https://openalex.org/W2981679558","https://openalex.org/W3133696950","https://openalex.org/W3157699413","https://openalex.org/W3160331490","https://openalex.org/W3182230372","https://openalex.org/W4243367342","https://openalex.org/W4308627565","https://openalex.org/W4313555233","https://openalex.org/W4360951492","https://openalex.org/W4367555203","https://openalex.org/W4386566925","https://openalex.org/W4386980851","https://openalex.org/W4400517951","https://openalex.org/W4404119199","https://openalex.org/W4409488311","https://openalex.org/W4411864770"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Imbalanced":[1],"class":[2,61],"distributions":[3],"pose":[4],"significant":[5],"challenges":[6],"in":[7,74,80,266,272,302],"document":[8,249],"classification,":[9],"but":[10,155],"which":[11,84],"balancing":[12,30,82,121,206,261,277],"methods":[13,31,165],"work":[14],"best":[15],"with":[16,58,95,174,185,227],"different":[17],"algorithms":[18],"remains":[19],"insufficiently":[20],"understood.":[21],"This":[22,242],"research":[23,243],"conducts":[24],"rigorous":[25],"statistical":[26,111],"analysis":[27],"of":[28,48,128,260,295],"five":[29,66],"(SMOTE,":[32],"ADASYN,":[33],"BorderlineSMOTE,":[34],"SMOTEENN,":[35],"SMOTETomek)":[36],"applied":[37],"to":[38,213],"twelve":[39,130],"machine":[40],"learning":[41],"classifiers.":[42],"We":[43],"use":[44],"a":[45,59,70],"novel":[46],"dataset":[47],"2,240":[49],"Turkish":[50,247],"institutional":[51,76,248,274],"documents":[52],"from":[53],"the":[54,81,129,133,196,245,257,267,293],"Social":[55],"Security":[56],"Institution":[57],"marginal":[60,268],"imbalance":[62,269],"(2.2:1":[63],"ratio)":[64],"across":[65,104,204,238],"functional":[67],"classifications":[68],"\u2013":[69],"regime":[71,270],"frequently":[72],"encountered":[73],"real":[75],"settings":[77],"yet":[78],"underexamined":[79],"literature,":[83],"has":[85],"concentrated":[86],"on":[87],"severely":[88],"imbalanced":[89],"benchmarks.":[90],"Through":[91],"stratified":[92],"10-fold":[93],"cross-validation":[94],"paired":[96],"t":[97],"-tests":[98],"and":[99,150,263,282],"Cohen\u2019s":[100,145],"d":[101,146],"effect-size":[102],"measurements":[103],"72":[105,240],"experimental":[106],"configurations":[107],"(yielding":[108],"60":[109],"pairwise":[110],"comparisons),":[112],"we":[113],"observed":[114,271],"algorithm-dependent":[115],"performance":[116,125,286],"differences":[117,230],"that":[118],"question":[119],"universal":[120,258],"assumptions.":[122],"SMOTEENN":[123],"reduced":[124],"for":[126,287],"ten":[127],"classifiers":[131],"at":[132],"p":[134,181,192,216],"<":[135,217],"0.05":[136],"level":[137],"(mean":[138,231],"\u0394":[139,176,187,233],"F":[140,177,188,209,234],"1":[141,178,189,210,235],"=":[142,147,179,182,190,193,211,236],"\u22120.0495,":[143],"mean":[144],"\u22121.57;":[148],"AdaBoost":[149,184],"Naive":[151],"Bayes":[152],"showed":[153,166],"negative":[154],"non-significant":[156],"changes),":[157],"while":[158],"alternative":[159],"techniques":[160],"produced":[161],"algorithm-specific":[162,296],"outcomes:":[163],"ensemble":[164],"only":[167],"descriptive,":[168],"non-statistically-significant":[169],"point":[170],"gains":[171],"(Random":[172],"Forest":[173],"SMOTE:":[175,186],"+0.0043,":[180],"0.470;":[183],"+0.0225,":[191],"0.174),":[194],"whereas":[195],"distance-based":[197],"K-Nearest":[198],"Neighbors":[199],"classifier":[200],"experienced":[201],"uniform":[202],"degradation":[203],"every":[205],"method":[207],"(\u0394":[208],"\u22120.0613":[212],"\u22120.0328,":[214],"all":[215,219,239],"0.05,":[218],"large":[220],"effects).":[221],"Independent":[222],"test":[223],"validation":[224,297],"confirmed":[225],"results":[226],"minimal":[228],"generalization":[229],"absolute":[232],"0.034":[237],"configurations).":[241],"introduces":[244],"first":[246],"classification":[250],"dataset,":[251,275],"provides":[252],"statistically":[253],"robust":[254],"evidence":[255],"questioning":[256],"effectiveness":[259],"techniques,":[262],"suggests":[264],"that,":[265],"this":[273],"automatic":[276],"may":[278,283],"not":[279],"be":[280],"necessary":[281],"even":[284],"degrade":[285],"certain":[288],"algorithm":[289],"families.":[290],"Findings":[291],"highlight":[292],"importance":[294],"rather":[298],"than":[299],"one-size-fits-all":[300],"approaches":[301],"resource-constrained":[303],"settings.":[304]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-07-11T00:00:00"}