{"id":"https://openalex.org/W2288871829","doi":"https://doi.org/10.1145/2808797.2809380","title":"Breaking the News","display_name":"Breaking the News","publication_year":2015,"publication_date":"2015-08-25","ids":{"openalex":"https://openalex.org/W2288871829","doi":"https://doi.org/10.1145/2808797.2809380","mag":"2288871829"},"language":"en","primary_location":{"id":"doi:10.1145/2808797.2809380","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808797.2809380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015","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/A5018128415","display_name":"Andreas Spitz","orcid":"https://orcid.org/0000-0002-5282-6133"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Spitz","raw_affiliation_strings":["Institute of Computer Science, Heidelberg University, Im Neuenheimer Feld 348, 69120 Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Heidelberg University, Im Neuenheimer Feld 348, 69120 Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061021795","display_name":"Michael Gertz","orcid":"https://orcid.org/0000-0003-4530-6110"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Gertz","raw_affiliation_strings":["Institute of Computer Science, Heidelberg University, Im Neuenheimer Feld 348, 69120 Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Heidelberg University, Im Neuenheimer Feld 348, 69120 Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1925,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.79936657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"274","last_page":"279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9736999869346619,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9599000215530396,"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/computer-science","display_name":"Computer science","score":0.7339232563972473},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.6013141870498657},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.588308572769165},{"id":"https://openalex.org/keywords/citation","display_name":"Citation","score":0.5838932991027832},{"id":"https://openalex.org/keywords/bibliometrics","display_name":"Bibliometrics","score":0.5436683297157288},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5301597714424133},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.49870729446411133},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4945850074291229},{"id":"https://openalex.org/keywords/citation-analysis","display_name":"Citation analysis","score":0.47265875339508057},{"id":"https://openalex.org/keywords/scientometrics","display_name":"Scientometrics","score":0.46201765537261963},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.36497312784194946},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35241812467575073},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11009609699249268},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.08110281825065613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7339232563972473},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6013141870498657},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.588308572769165},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.5838932991027832},{"id":"https://openalex.org/C178315738","wikidata":"https://www.wikidata.org/wiki/Q603441","display_name":"Bibliometrics","level":2,"score":0.5436683297157288},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5301597714424133},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.49870729446411133},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4945850074291229},{"id":"https://openalex.org/C105345328","wikidata":"https://www.wikidata.org/wiki/Q206276","display_name":"Citation analysis","level":3,"score":0.47265875339508057},{"id":"https://openalex.org/C525823164","wikidata":"https://www.wikidata.org/wiki/Q472342","display_name":"Scientometrics","level":2,"score":0.46201765537261963},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.36497312784194946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35241812467575073},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11009609699249268},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08110281825065613},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2808797.2809380","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2808797.2809380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W19838944","https://openalex.org/W84889933","https://openalex.org/W170821200","https://openalex.org/W1495063011","https://openalex.org/W1572923654","https://openalex.org/W1578007978","https://openalex.org/W1847729410","https://openalex.org/W1997168088","https://openalex.org/W2003510653","https://openalex.org/W2033193852","https://openalex.org/W2053549370","https://openalex.org/W2063294070","https://openalex.org/W2064796447","https://openalex.org/W2092379971","https://openalex.org/W2109603058","https://openalex.org/W2111708605","https://openalex.org/W2123171175","https://openalex.org/W2123328057","https://openalex.org/W2124637492","https://openalex.org/W2127387319","https://openalex.org/W2127492100","https://openalex.org/W2128438887","https://openalex.org/W2140540364","https://openalex.org/W2149786015","https://openalex.org/W2151866568","https://openalex.org/W2162340532","https://openalex.org/W3106377737","https://openalex.org/W3122427042","https://openalex.org/W3141829038","https://openalex.org/W3142588439","https://openalex.org/W4236779576","https://openalex.org/W6603453264"],"related_works":["https://openalex.org/W4318064389","https://openalex.org/W2608471332","https://openalex.org/W2404918212","https://openalex.org/W3013717264","https://openalex.org/W2188838022","https://openalex.org/W2349928826","https://openalex.org/W2765483308","https://openalex.org/W1992422757","https://openalex.org/W2853465312","https://openalex.org/W2588241638"],"abstract_inverted_index":{"Networks":[0],"of":[1,10,29,38,52,63,69,92,107,118,136,156,166],"online":[2,93,167],"news":[3,94,119,168],"articles":[4,95,120],"and":[5,32,55,75,127,141,161],"blog":[6],"posts":[7],"are":[8,33,61],"some":[9],"the":[11,36,50,64,87,105,134,151,154,164],"most":[12],"commonly":[13],"used":[14,34],"data":[15,116],"sets":[16],"in":[17,49,138,163],"network":[18,30,71],"science.":[19],"As":[20],"a":[21,26,115],"result,":[22],"they":[23],"have":[24,76],"become":[25],"vital":[27],"piece":[28],"analysis":[31,51,72,165],"for":[35,79],"evaluation":[37],"algorithms":[39],"that":[40,86],"work":[41],"on":[42],"large":[43],"networks,":[44,148],"or":[45],"serve":[46],"as":[47],"examples":[48],"information":[53,131,137],"diffusion":[54],"propagation.":[56,169],"Similarly,":[57],"scientific":[58,101,146],"citation":[59,102,147],"networks":[60,91,103],"part":[62],"bedrock":[65],"upon":[66],"which":[67],"much":[68],"modern":[70],"is":[73,110,124,142],"built":[74],"been":[77],"studied":[78],"decades.":[80],"In":[81],"this":[82],"paper,":[83],"we":[84],"show":[85],"backbone":[88],"inherent":[89],"to":[90,100,133,145,153],"shares":[96],"significant":[97],"structural":[98],"similarities":[99],"once":[104],"noise":[106],"spurious":[108],"links":[109],"stripped":[111],"away.":[112],"We":[113],"present":[114],"set":[117],"that,":[121],"while":[122],"it":[123],"extremely":[125],"sparse":[126],"lightweight,":[128],"still":[129],"contains":[130],"relevant":[132],"propagation":[135],"mass":[139],"media":[140],"remarkably":[143],"similar":[144],"thus":[149],"opening":[150],"door":[152],"use":[155],"established":[157],"methodologies":[158],"from":[159],"scientometrics":[160],"bibliometrics":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2016-06-24T00:00:00"}