{"id":"https://openalex.org/W4404133478","doi":"https://doi.org/10.1109/compeng60905.2024.10741428","title":"Detecting Influential Nodes with Centrality Measures via Random Forest in Social Networks","display_name":"Detecting Influential Nodes with Centrality Measures via Random Forest in Social Networks","publication_year":2024,"publication_date":"2024-07-22","ids":{"openalex":"https://openalex.org/W4404133478","doi":"https://doi.org/10.1109/compeng60905.2024.10741428"},"language":"en","primary_location":{"id":"doi:10.1109/compeng60905.2024.10741428","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/compeng60905.2024.10741428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Workshop on Complexity in Engineering (COMPENG)","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/A5095787569","display_name":"Ndeye Khady Aidara","orcid":null},"institutions":[{"id":"https://openalex.org/I112713213","display_name":"Universit\u00e9 Gaston Berger","ror":"https://ror.org/01jp0tk64","country_code":"SN","type":"education","lineage":["https://openalex.org/I112713213"]}],"countries":["SN"],"is_corresponding":true,"raw_author_name":"Ndeye Khady Aidara","raw_affiliation_strings":["Gaston Berger University,LACCA LAB,Saint-Louis,Senegal"],"affiliations":[{"raw_affiliation_string":"Gaston Berger University,LACCA LAB,Saint-Louis,Senegal","institution_ids":["https://openalex.org/I112713213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085400794","display_name":"Issa Moussa Diop","orcid":"https://orcid.org/0000-0001-5624-319X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Issa Moussa Diop","raw_affiliation_strings":["C&#x00F4;te d&#x2019;Azur University,DS4H, I3S,Nice,France"],"affiliations":[{"raw_affiliation_string":"C&#x00F4;te d&#x2019;Azur University,DS4H, I3S,Nice,France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016796799","display_name":"Ch\u00e9rif Diallo","orcid":"https://orcid.org/0000-0001-6606-7337"},"institutions":[{"id":"https://openalex.org/I112713213","display_name":"Universit\u00e9 Gaston Berger","ror":"https://ror.org/01jp0tk64","country_code":"SN","type":"education","lineage":["https://openalex.org/I112713213"]}],"countries":["SN"],"is_corresponding":false,"raw_author_name":"Cherif Diallo","raw_affiliation_strings":["Gaston Berger University,LACCA LAB,Saint-Louis,Senegal"],"affiliations":[{"raw_affiliation_string":"Gaston Berger University,LACCA LAB,Saint-Louis,Senegal","institution_ids":["https://openalex.org/I112713213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006125158","display_name":"Hocine Cherifi","orcid":"https://orcid.org/0000-0001-9124-4921"},"institutions":[{"id":"https://openalex.org/I177064439","display_name":"Universit\u00e9 de Bourgogne","ror":"https://ror.org/03k1bsr36","country_code":"FR","type":"education","lineage":["https://openalex.org/I177064439"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hocine Cherifi","raw_affiliation_strings":["Universit&#x00E9; de Bourgogne,ICB UMR 6303 CNRS,Dijon,France,21078"],"affiliations":[{"raw_affiliation_string":"Universit&#x00E9; de Bourgogne,ICB UMR 6303 CNRS,Dijon,France,21078","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I177064439"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5095787569"],"corresponding_institution_ids":["https://openalex.org/I112713213"],"apc_list":null,"apc_paid":null,"fwci":0.2976,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57028151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9890999794006348,"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":0.9890999794006348,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9843000173568726,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/centrality","display_name":"Centrality","score":0.8606966137886047},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6764825582504272},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6000437140464783},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34135133028030396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3129206895828247},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12921449542045593},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11104258894920349}],"concepts":[{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.8606966137886047},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6764825582504272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000437140464783},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34135133028030396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3129206895828247},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12921449542045593},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11104258894920349}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/compeng60905.2024.10741428","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/compeng60905.2024.10741428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Workshop on Complexity in Engineering (COMPENG)","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":44,"referenced_works":["https://openalex.org/W1128809682","https://openalex.org/W1536060130","https://openalex.org/W1992250165","https://openalex.org/W2171707538","https://openalex.org/W2263392086","https://openalex.org/W2580734735","https://openalex.org/W2609335210","https://openalex.org/W2612872092","https://openalex.org/W2789257827","https://openalex.org/W2802643674","https://openalex.org/W2883365145","https://openalex.org/W2896311902","https://openalex.org/W2906484232","https://openalex.org/W2922073769","https://openalex.org/W2951941886","https://openalex.org/W2963689597","https://openalex.org/W2968179778","https://openalex.org/W3004544135","https://openalex.org/W3007653990","https://openalex.org/W3029971898","https://openalex.org/W3040437829","https://openalex.org/W3043094543","https://openalex.org/W3043948261","https://openalex.org/W3045237327","https://openalex.org/W3088325818","https://openalex.org/W3094457149","https://openalex.org/W3096922567","https://openalex.org/W3122910277","https://openalex.org/W3196993664","https://openalex.org/W3200474001","https://openalex.org/W3210619801","https://openalex.org/W4206098349","https://openalex.org/W4210997308","https://openalex.org/W4229454579","https://openalex.org/W4287829537","https://openalex.org/W4287829721","https://openalex.org/W4290708032","https://openalex.org/W4293491684","https://openalex.org/W4322775715","https://openalex.org/W4372313732","https://openalex.org/W4400771444","https://openalex.org/W6640581393","https://openalex.org/W6774097426","https://openalex.org/W6840924649"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4229078645","https://openalex.org/W1977345676","https://openalex.org/W4282032776","https://openalex.org/W2047552823","https://openalex.org/W4321606905","https://openalex.org/W3130445735","https://openalex.org/W2105110616"],"abstract_inverted_index":{"Identifying":[0],"influential":[1,163],"nodes":[2,164],"in":[3,30,165],"networks":[4],"is":[5],"a":[6,55,69,155],"crucial":[7],"task":[8],"with":[9,134],"many":[10],"applications":[11],"across":[12,148],"various":[13,166],"domains.":[14],"Traditional":[15],"centrality":[16,62],"measures,":[17],"while":[18],"insightful,":[19],"often":[20],"fail":[21],"to":[22,96,139],"capture":[23],"the":[24,97,109,112,116,122,170],"true":[25],"influence":[26],"of":[27,124,137],"nodes,":[28],"especially":[29],"complex":[31],"networks.":[32],"Machine":[33],"learning":[34],"techniques":[35],"can":[36],"potentially":[37],"incorporate":[38],"diverse":[39],"node":[40],"features,":[41],"but":[42],"their":[43],"effectiveness":[44,123],"relies":[45],"heavily":[46],"on":[47,105],"feature":[48],"engineering.":[49],"In":[50],"this":[51],"study,":[52],"we":[53],"propose":[54],"hybrid":[56],"methodology":[57],"that":[58],"synergistically":[59],"combines":[60],"well-established":[61],"measures":[63],"as":[64,93],"topological":[65],"features":[66,95],"and":[67,83,115,141,146,157],"employs":[68],"powerful":[70],"Random":[71,98,127],"Forest":[72,99,128],"classifier.":[73],"Our":[74],"approach":[75],"extracts":[76],"degree,":[77],"betweenness,":[78],"closeness,":[79],"eigenvector":[80],"centrality,":[81],"PageRank,":[82],"clustering":[84],"coefficients":[85],"for":[86,160,172],"each":[87],"node,":[88],"which":[89],"are":[90],"then":[91],"used":[92],"input":[94],"model.":[100],"We":[101],"evaluate":[102],"our":[103,125],"method":[104],"three":[106],"real-world":[107],"networks:":[108],"Cora":[110],"dataset,":[111,114],"CA-HepTh":[113],"Facebook":[117],"dataset.":[118],"The":[119,151],"results":[120],"demonstrate":[121],"centrality-based":[126],"approach,":[129],"outperforming":[130],"state-of-the-art":[131],"baseline":[132],"methods":[133],"an":[135],"accuracy":[136],"up":[138],"97.18%":[140],"achieving":[142],"high":[143],"precision,":[144],"recall,":[145],"F1-scores":[147],"all":[149],"datasets.":[150],"proposed":[152],"technique":[153],"offers":[154],"robust":[156],"generalizable":[158],"solution":[159],"accurately":[161],"identifying":[162],"network":[167],"structures,":[168],"paving":[169],"way":[171],"numerous":[173],"practical":[174],"applications.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
