{"id":"https://openalex.org/W2766528771","doi":"https://doi.org/10.1007/s40595-017-0097-1","title":"RETRACTED ARTICLE: Concordance-based Kendall\u2019s correlation for computationally-light vs. computationally-heavy centrality metrics: lower bound for correlation","display_name":"RETRACTED ARTICLE: Concordance-based Kendall\u2019s correlation for computationally-light vs. computationally-heavy centrality metrics: lower bound for correlation","publication_year":2017,"publication_date":"2017-06-28","ids":{"openalex":"https://openalex.org/W2766528771","doi":"https://doi.org/10.1007/s40595-017-0097-1","mag":"2766528771"},"language":"en","primary_location":{"id":"doi:10.1007/s40595-017-0097-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40595-017-0097-1","pdf_url":null,"source":{"id":"https://openalex.org/S2486636169","display_name":"Vietnam Journal of Computer Science","issn_l":"2196-8888","issn":["2196-8888","2196-8896"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Vietnam Journal of Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1007/s40595-017-0097-1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022212660","display_name":"Natarajan Meghanathan","orcid":"https://orcid.org/0000-0001-8565-4086"},"institutions":[{"id":"https://openalex.org/I61937129","display_name":"Jackson State University","ror":"https://ror.org/01ecnnp60","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I61937129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Natarajan Meghanathan","raw_affiliation_strings":["Computer Science, Jackson State University, Jackson, MS, 39217, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science, Jackson State University, Jackson, MS, 39217, USA","institution_ids":["https://openalex.org/I61937129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022212660"],"corresponding_institution_ids":["https://openalex.org/I61937129"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15497122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"1","first_page":"83","last_page":"83"},"is_retracted":true,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.8836435079574585},{"id":"https://openalex.org/keywords/betweenness-centrality","display_name":"Betweenness centrality","score":0.6664881110191345},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6227551102638245},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6143160462379456},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5545936822891235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5540986657142639},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.5145272612571716},{"id":"https://openalex.org/keywords/concordance","display_name":"Concordance","score":0.4763398766517639},{"id":"https://openalex.org/keywords/spearmans-rank-correlation-coefficient","display_name":"Spearman's rank correlation coefficient","score":0.4570602774620056},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4353228807449341},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.4257124960422516},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.42476823925971985},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.41064757108688354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2815072536468506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24324989318847656},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.2397424876689911}],"concepts":[{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.8836435079574585},{"id":"https://openalex.org/C117045392","wikidata":"https://www.wikidata.org/wiki/Q4899215","display_name":"Betweenness centrality","level":3,"score":0.6664881110191345},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6227551102638245},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6143160462379456},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5545936822891235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5540986657142639},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5145272612571716},{"id":"https://openalex.org/C160798450","wikidata":"https://www.wikidata.org/wiki/Q4230870","display_name":"Concordance","level":2,"score":0.4763398766517639},{"id":"https://openalex.org/C159744936","wikidata":"https://www.wikidata.org/wiki/Q1126730","display_name":"Spearman's rank correlation coefficient","level":2,"score":0.4570602774620056},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4353228807449341},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.4257124960422516},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42476823925971985},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.41064757108688354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2815072536468506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24324989318847656},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2397424876689911},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s40595-017-0097-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40595-017-0097-1","pdf_url":null,"source":{"id":"https://openalex.org/S2486636169","display_name":"Vietnam Journal of Computer Science","issn_l":"2196-8888","issn":["2196-8888","2196-8896"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Vietnam Journal of Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9386581ac16e42cebf9800902bf9b268","is_oa":true,"landing_page_url":"https://doaj.org/article/9386581ac16e42cebf9800902bf9b268","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Vietnam Journal of Computer Science, Vol 5, Iss 1, Pp 83-83 (2017)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40595-017-0097-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40595-017-0097-1","pdf_url":null,"source":{"id":"https://openalex.org/S2486636169","display_name":"Vietnam Journal of Computer Science","issn_l":"2196-8888","issn":["2196-8888","2196-8896"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Vietnam Journal of Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W73486220","https://openalex.org/W118100147","https://openalex.org/W331086104","https://openalex.org/W1481302545","https://openalex.org/W1504901897","https://openalex.org/W1596621343","https://openalex.org/W1607795029","https://openalex.org/W1964130041","https://openalex.org/W1967140769","https://openalex.org/W1971421925","https://openalex.org/W1971937094","https://openalex.org/W1987079028","https://openalex.org/W2010033398","https://openalex.org/W2013772221","https://openalex.org/W2015953751","https://openalex.org/W2029542214","https://openalex.org/W2056944867","https://openalex.org/W2058608134","https://openalex.org/W2062261637","https://openalex.org/W2081515376","https://openalex.org/W2087194317","https://openalex.org/W2090200605","https://openalex.org/W2094234423","https://openalex.org/W2096141816","https://openalex.org/W2100618934","https://openalex.org/W2102490385","https://openalex.org/W2105201056","https://openalex.org/W2116819994","https://openalex.org/W2120260128","https://openalex.org/W2130790725","https://openalex.org/W2142170653","https://openalex.org/W2143989965","https://openalex.org/W2149349114","https://openalex.org/W2153383412","https://openalex.org/W2154656661","https://openalex.org/W2160938187","https://openalex.org/W2166951268","https://openalex.org/W2171707538","https://openalex.org/W2220098999","https://openalex.org/W2301321762","https://openalex.org/W2319381411","https://openalex.org/W2427462040","https://openalex.org/W2466523754","https://openalex.org/W2473333158","https://openalex.org/W2476680721","https://openalex.org/W2538283942","https://openalex.org/W2560380522","https://openalex.org/W2588971764","https://openalex.org/W2785756223","https://openalex.org/W2797904114","https://openalex.org/W2913725584","https://openalex.org/W3100069540","https://openalex.org/W3101413764","https://openalex.org/W3102430438","https://openalex.org/W3105709855","https://openalex.org/W3129907499","https://openalex.org/W3145128584","https://openalex.org/W4206349042","https://openalex.org/W4212863801","https://openalex.org/W4237036574","https://openalex.org/W4238452917","https://openalex.org/W4246219036","https://openalex.org/W4247674577","https://openalex.org/W4255390387","https://openalex.org/W6606676520","https://openalex.org/W6727560376","https://openalex.org/W6812340227"],"related_works":["https://openalex.org/W1973509935","https://openalex.org/W4389076551","https://openalex.org/W2097992793","https://openalex.org/W2107855069","https://openalex.org/W2611574733","https://openalex.org/W2241641394","https://openalex.org/W2140653560","https://openalex.org/W2348831795","https://openalex.org/W2514739320","https://openalex.org/W4312461432"],"abstract_inverted_index":{"We":[0,88,152],"identify":[1],"three":[2,110,159],"different":[3],"levels":[4,111,134],"of":[5,51,76,97,107,112,135,165,194],"correlation":[6,35,99,113,120,127,136,142,150,160],"(pair-wise":[7],"relative":[8,49,74,93],"ordering,":[9],"network-wide":[10],"ranking":[11],"and":[12,24,59,114,144,171,179,186],"linear":[13],"regression)":[14],"that":[15,90,116],"could":[16,37,46],"be":[17,38,123],"assessed":[18],"between":[19,100,162],"a":[20,25,68,84,191],"computationally-light":[21,69,169],"centrality":[22,27,70,86,101,166,177,185,188],"metric":[23,28,71],"computationally-heavy":[26,85,181],"for":[29,190],"real-world":[30,196],"networks.":[31,197],"The":[32],"Kendall's":[33,118],"concordance-based":[34,119],"measure":[36],"used":[39],"to":[40,67,83],"quantitatively":[41],"assess":[42],"how":[43],"well":[44],"we":[45],"consider":[47],"the":[48,73,77,91,98,104,109,117,126,131,145,158,168,180],"ordering":[50,75,94],"two":[52,79,163],"vertices":[53,80],"v":[55,61],"i":[56],"j":[62],"with":[65,81,130],"respect":[66,82],"as":[72],"same":[78],"metric.":[87],"hypothesize":[89],"pair-wise":[92],"(concordance)-based":[95],"assessment":[96],"metrics":[102,178,189],"is":[103],"most":[105],"strictest":[106],"all":[108],"claim":[115],"coefficient":[121,128,143,174],"will":[122],"lower":[124],"than":[125],"observed":[129],"more":[132],"relaxed":[133],"measures":[137],"(linear":[138],"regression-based":[139],"Pearson's":[140],"product-moment":[141],"network":[146],"wide":[147],"ranking-based":[148],"Spearman's":[149],"coefficient).":[151],"validate":[153],"our":[154],"hypothesis":[155],"by":[156],"evaluating":[157],"coefficients":[161],"sets":[164],"metrics:":[167],"degree":[170,176],"local":[172],"clustering":[173],"complement-based":[175],"eigenvector":[182],"centrality,":[183],"betweenness":[184],"closeness":[187],"diverse":[192],"collection":[193],"50":[195]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
