{"id":"https://openalex.org/W2887557209","doi":"https://doi.org/10.1109/icc.2018.8422245","title":"Exponentially Twisted Sampling for Centrality Analysis in Attributed Networks","display_name":"Exponentially Twisted Sampling for Centrality Analysis in Attributed Networks","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2887557209","doi":"https://doi.org/10.1109/icc.2018.8422245","mag":"2887557209"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2018.8422245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications (ICC)","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/A5111005302","display_name":"Cheng-Hsun Chang","orcid":"https://orcid.org/0009-0002-0609-3490"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Cheng-Hsun Chang","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016945609","display_name":"Cheng\u2010Shang Chang","orcid":"https://orcid.org/0000-0002-5386-4756"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Cheng-Shang Chang","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043136272","display_name":"Duan\u2010Shin Lee","orcid":"https://orcid.org/0000-0003-4578-2002"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Duan-Shin Lee","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081012062","display_name":"Ping-En Lu","orcid":"https://orcid.org/0000-0002-1352-0983"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ping-En Lu","raw_affiliation_strings":["Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C"],"affiliations":[{"raw_affiliation_string":"Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5111005302"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10792509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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/T10557","display_name":"Social Media and Politics","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"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/centrality","display_name":"Centrality","score":0.894842803478241},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.631318211555481},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5857686996459961},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5841006636619568},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.552510678768158},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5455729961395264},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5440511107444763},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.5426620841026306},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5035895705223083},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.48151859641075134},{"id":"https://openalex.org/keywords/exponential-growth","display_name":"Exponential growth","score":0.44781258702278137},{"id":"https://openalex.org/keywords/path-analysis","display_name":"Path analysis (statistics)","score":0.4235721230506897},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.42107492685317993},{"id":"https://openalex.org/keywords/network-science","display_name":"Network science","score":0.4162042438983917},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4142306447029114},{"id":"https://openalex.org/keywords/social-network-analysis","display_name":"Social network analysis","score":0.41077959537506104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30377012491226196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23195195198059082},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1590486764907837},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14891690015792847},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07826745510101318}],"concepts":[{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.894842803478241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.631318211555481},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5857686996459961},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5841006636619568},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.552510678768158},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5455729961395264},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5440511107444763},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.5426620841026306},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5035895705223083},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.48151859641075134},{"id":"https://openalex.org/C75235859","wikidata":"https://www.wikidata.org/wiki/Q582659","display_name":"Exponential growth","level":2,"score":0.44781258702278137},{"id":"https://openalex.org/C82793941","wikidata":"https://www.wikidata.org/wiki/Q1046024","display_name":"Path analysis (statistics)","level":2,"score":0.4235721230506897},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.42107492685317993},{"id":"https://openalex.org/C137753397","wikidata":"https://www.wikidata.org/wiki/Q2434424","display_name":"Network science","level":3,"score":0.4162042438983917},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4142306447029114},{"id":"https://openalex.org/C114713312","wikidata":"https://www.wikidata.org/wiki/Q7551269","display_name":"Social network analysis","level":3,"score":0.41077959537506104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30377012491226196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23195195198059082},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1590486764907837},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14891690015792847},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07826745510101318},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2018.8422245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1580385316","https://openalex.org/W1582443468","https://openalex.org/W1856487264","https://openalex.org/W1875112053","https://openalex.org/W1971937094","https://openalex.org/W1978905175","https://openalex.org/W2056944867","https://openalex.org/W2066636486","https://openalex.org/W2069153192","https://openalex.org/W2076219102","https://openalex.org/W2099111195","https://openalex.org/W2103135182","https://openalex.org/W2152284345","https://openalex.org/W2170344111","https://openalex.org/W2210387432","https://openalex.org/W2740686884","https://openalex.org/W2963816597","https://openalex.org/W4206809386","https://openalex.org/W6634721320"],"related_works":["https://openalex.org/W1515007544","https://openalex.org/W2941456333","https://openalex.org/W2904868555","https://openalex.org/W4383560764","https://openalex.org/W1554338108","https://openalex.org/W3134928396","https://openalex.org/W1663961612","https://openalex.org/W3102208438","https://openalex.org/W2558990382","https://openalex.org/W2022996068"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,85,111,144],"conduct":[4],"centrality":[5,34],"analysis":[6,35],"for":[7,51],"attributed":[8,11,68,139],"networks.":[9,162],"An":[10],"network,":[12],"as":[13,47],"a":[14,17,37,43,48,118,130,134,152],"generalization":[15],"of":[16,29,36,89,136],"graph,":[18],"has":[19],"node":[20,56,142],"attributes":[21,24,57,60],"and":[22,31,58,94,124,180],"edge":[23,59],"that":[25,156],"represent":[26],"the":[27,52,63,75,80,87,102,113,125,177,181],"\"features''":[28],"nodes":[30],"edges.":[32],"Traditionally,":[33],"graph":[38],"is":[39],"done":[40],"by":[41,116,128,150,172],"providing":[42],"sampling":[44,64,77,92,103],"method,":[45],"such":[46,161],"random":[49],"walk,":[50],"graph.":[53,82],"To":[54],"take":[55],"into":[61],"account,":[62],"method":[65,78,104],"in":[66,79,160],"an":[67],"network":[69],"needs":[70],"to":[71,99,167],"be":[72,106],"twisted":[73,91],"from":[74,121,133],"original":[76],"underlining":[81],"For":[83,108,138],"this,":[84],"consider":[86],"family":[88],"exponentially":[90],"methods":[93],"propose":[95],"using":[96,117,129,151,173],"path":[97,119,131,154],"measures":[98],"specify":[100],"how":[101],"should":[105],"twisted.":[107],"signed":[109],"networks,":[110],"define":[112,146],"influence":[114,148,158],"centralities":[115,127,149,171],"measure":[120,132,155],"opinions":[122],"dynamics":[123],"trust":[126],"chain":[135],"trust.":[137],"networks":[140],"with":[141],"attributes,":[143],"also":[145],"advertisement-specific":[147],"specific":[153],"models":[157],"cascades":[159],"Various":[163],"experiments":[164],"are":[165],"conducted":[166],"further":[168],"illustrate":[169],"these":[170],"two":[174],"real":[175],"datasets:":[176],"political":[178],"blogs":[179],"MemeTracker":[182],"dataset.":[183]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}