{"id":"https://openalex.org/W4299624667","doi":"https://doi.org/10.1109/tcss.2022.3195525","title":"Influential Node Detection and Ranking With Fusion of Heterogeneous Social Media Information","display_name":"Influential Node Detection and Ranking With Fusion of Heterogeneous Social Media Information","publication_year":2022,"publication_date":"2022-08-09","ids":{"openalex":"https://openalex.org/W4299624667","doi":"https://doi.org/10.1109/tcss.2022.3195525"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2022.3195525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2022.3195525","pdf_url":null,"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":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101508225","display_name":"Seema Rani","orcid":"https://orcid.org/0000-0001-9470-9851"},"institutions":[{"id":"https://openalex.org/I51452335","display_name":"Panjab University","ror":"https://ror.org/04p2sbk06","country_code":"IN","type":"education","lineage":["https://openalex.org/I51452335"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Seema Rani","raw_affiliation_strings":["Computer Science and Engineering Department, University Institute of Engineering and Technology, Panjab University, Chandigarh, India"],"raw_orcid":"https://orcid.org/0000-0001-9470-9851","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, University Institute of Engineering and Technology, Panjab University, Chandigarh, India","institution_ids":["https://openalex.org/I51452335"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045085821","display_name":"Mukesh Kumar","orcid":"https://orcid.org/0000-0002-4920-670X"},"institutions":[{"id":"https://openalex.org/I51452335","display_name":"Panjab University","ror":"https://ror.org/04p2sbk06","country_code":"IN","type":"education","lineage":["https://openalex.org/I51452335"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mukesh Kumar","raw_affiliation_strings":["Computer Science and Engineering Department, University Institute of Engineering and Technology, Panjab University, Chandigarh, India"],"raw_orcid":"https://orcid.org/0000-0002-4920-670X","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, University Institute of Engineering and Technology, Panjab University, Chandigarh, India","institution_ids":["https://openalex.org/I51452335"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6278,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.83789073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"10","issue":"4","first_page":"1852","last_page":"1874"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9955999851226807,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6994743347167969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6471460461616516},{"id":"https://openalex.org/keywords/analytic-hierarchy-process","display_name":"Analytic hierarchy process","score":0.6160776615142822},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5971784591674805},{"id":"https://openalex.org/keywords/topsis","display_name":"TOPSIS","score":0.5672522187232971},{"id":"https://openalex.org/keywords/multiple-criteria-decision-analysis","display_name":"Multiple-criteria decision analysis","score":0.5401100516319275},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5368986129760742},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4772246181964874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47248998284339905},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4711923599243164},{"id":"https://openalex.org/keywords/spearmans-rank-correlation-coefficient","display_name":"Spearman's rank correlation coefficient","score":0.4272564649581909},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4148060381412506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.388834685087204},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.2738589644432068},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2173321545124054},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11113867163658142}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6994743347167969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6471460461616516},{"id":"https://openalex.org/C87345402","wikidata":"https://www.wikidata.org/wiki/Q485202","display_name":"Analytic hierarchy process","level":2,"score":0.6160776615142822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5971784591674805},{"id":"https://openalex.org/C51566761","wikidata":"https://www.wikidata.org/wiki/Q1235853","display_name":"TOPSIS","level":2,"score":0.5672522187232971},{"id":"https://openalex.org/C11105738","wikidata":"https://www.wikidata.org/wiki/Q1895805","display_name":"Multiple-criteria decision analysis","level":2,"score":0.5401100516319275},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5368986129760742},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4772246181964874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47248998284339905},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4711923599243164},{"id":"https://openalex.org/C159744936","wikidata":"https://www.wikidata.org/wiki/Q1126730","display_name":"Spearman's rank correlation coefficient","level":2,"score":0.4272564649581909},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4148060381412506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.388834685087204},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2738589644432068},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2173321545124054},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11113867163658142},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcss.2022.3195525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2022.3195525","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G570969262","display_name":null,"funder_award_id":"09/135(0745)/2016-EMR-I","funder_id":"https://openalex.org/F4320320682","funder_display_name":"Council for Scientific and Industrial Research, South Africa"}],"funders":[{"id":"https://openalex.org/F4320320682","display_name":"Council for Scientific and Industrial Research, South Africa","ror":"https://ror.org/05j00sr48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W1533674501","https://openalex.org/W1595267951","https://openalex.org/W1606375300","https://openalex.org/W1807089695","https://openalex.org/W1890189454","https://openalex.org/W1971941321","https://openalex.org/W1981123380","https://openalex.org/W1988183975","https://openalex.org/W1988680180","https://openalex.org/W1992250165","https://openalex.org/W1992392028","https://openalex.org/W1994320166","https://openalex.org/W2004698524","https://openalex.org/W2005907218","https://openalex.org/W2011975873","https://openalex.org/W2012557827","https://openalex.org/W2019243719","https://openalex.org/W2024224210","https://openalex.org/W2027135291","https://openalex.org/W2042102899","https://openalex.org/W2042123098","https://openalex.org/W2050766178","https://openalex.org/W2061820396","https://openalex.org/W2062420311","https://openalex.org/W2065851162","https://openalex.org/W2074617510","https://openalex.org/W2078728013","https://openalex.org/W2078844161","https://openalex.org/W2081805563","https://openalex.org/W2083842271","https://openalex.org/W2086243891","https://openalex.org/W2098005762","https://openalex.org/W2120589327","https://openalex.org/W2121035174","https://openalex.org/W2124142520","https://openalex.org/W2128679907","https://openalex.org/W2146699143","https://openalex.org/W2158478952","https://openalex.org/W2159863842","https://openalex.org/W2166293769","https://openalex.org/W2169149732","https://openalex.org/W2396727997","https://openalex.org/W2411562388","https://openalex.org/W2464692305","https://openalex.org/W2476716989","https://openalex.org/W2534133409","https://openalex.org/W2592164301","https://openalex.org/W2616583680","https://openalex.org/W2761865950","https://openalex.org/W2770752180","https://openalex.org/W2783479181","https://openalex.org/W2785020610","https://openalex.org/W2792932854","https://openalex.org/W2797495909","https://openalex.org/W2890145845","https://openalex.org/W2900934918","https://openalex.org/W2900941345","https://openalex.org/W2903499520","https://openalex.org/W2909195503","https://openalex.org/W2936792392","https://openalex.org/W2955290266","https://openalex.org/W2963913979","https://openalex.org/W2971865300","https://openalex.org/W2973688580","https://openalex.org/W2978422749","https://openalex.org/W2982735567","https://openalex.org/W3003596513","https://openalex.org/W3037311948","https://openalex.org/W3098164384","https://openalex.org/W3098409608","https://openalex.org/W3103589660","https://openalex.org/W3125511207","https://openalex.org/W3128140448","https://openalex.org/W3135327446","https://openalex.org/W3137606360","https://openalex.org/W3138435577","https://openalex.org/W3150478326","https://openalex.org/W3158448155","https://openalex.org/W3169860459","https://openalex.org/W3199514851","https://openalex.org/W4210386997","https://openalex.org/W4226227790","https://openalex.org/W4239181501","https://openalex.org/W6632445351"],"related_works":["https://openalex.org/W3006483227","https://openalex.org/W4235282010","https://openalex.org/W2142071684","https://openalex.org/W2385413488","https://openalex.org/W2355536739","https://openalex.org/W2322700324","https://openalex.org/W2295782676","https://openalex.org/W2351959113","https://openalex.org/W4381430929","https://openalex.org/W2140626576"],"abstract_inverted_index":{"Identification":[0],"of":[1,8,20,30,49,53,73,99,106,147,175,232],"influential":[2,74,120,177],"nodes":[3,55,75],"has":[4,91],"emerged":[5],"as":[6,137],"one":[7],"the":[9,17,31,39,47,50,54,71,77,85,100,128,138,143,160,168,176,187,199,207,211,220,230,233],"major":[10],"challenges,":[11],"especially":[12],"after":[13],"their":[14,58],"use":[15],"in":[16,26,34,46,76,94],"rapid":[18],"propagation":[19],"information,":[21],"epidemics,":[22],"and":[23,60,113,123,159,173,206],"so":[24],"on":[25,210],"social":[27],"media.":[28],"Most":[29],"previous":[32],"works":[33],"this":[35,95],"field":[36],"deal":[37],"with":[38,238],"homogeneous":[40],"interactions":[41,65,82],"that":[42,219],"are":[43,125,165,227],"not":[44],"pertinent":[45],"determination":[48],"accurate":[51],"context":[52],"due":[56],"to":[57,67,151,185,192],"noisy":[59],"sparse":[61],"nature.":[62],"Hence,":[63],"heterogeneous":[64,81,116],"need":[66],"be":[68],"explored":[69,166],"for":[70,127,145,167,171],"identification":[72,172],"network.":[78],"To":[79],"consider":[80],"available":[83],"within":[84],"network,":[86],"a":[87,103],"multilayer":[88],"network":[89,101,162],"(ML)":[90],"been":[92],"designed":[93,129],"work.":[96,189],"Each":[97],"layer":[98],"represents":[102],"particular":[104],"type":[105],"interaction,":[107],"e.g.,":[108],"upload,":[109],"comment,":[110],"retweet,":[111],"reply,":[112],"mention.":[114],"A":[115],"degree":[117],"ranking":[118,124,174],"(HDR)-based":[119],"nodes\u2019":[121],"detection":[122],"proposed":[126,169,188,225,234],"ML.":[130],"Furthermore,":[131,229],"multiple-criteria":[132],"decision-making":[133],"(MCDM)":[134],"methods,":[135,216],"such":[136],"analytic":[139,161],"hierarchy":[140],"process":[141,163],"(AHP),":[142],"technique":[144],"order":[146],"preference":[148],"by":[149,214,223],"similarity":[150],"ideal":[152],"solution":[153],"(TOPSIS),":[154],"fuzzy":[155,157],"AHP,":[156],"TOPSIS,":[158],"(ANP),":[164],"ML":[170],"nodes.":[178],"The":[179],"susceptible\u2013infected\u2013recovered":[180],"(SIR)":[181],"model":[182],"is":[183,196,236],"used":[184],"evaluate":[186],"In":[190],"addition":[191],"this,":[193],"statistical":[194],"analysis":[195],"performed":[197],"using":[198],"Pearson":[200],"correlation,":[201,203,205],"Kendall\u2019s":[202],"Spearman\u2019s":[204],"Friedman":[208],"test":[209],"ranks":[212],"generated":[213,222],"different":[215,224],"which":[217],"shows":[218],"results":[221],"methods":[226],"consistent.":[228],"performance":[231],"method":[235],"compared":[237],"state-of-the-art":[239],"approaches.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}