{"id":"https://openalex.org/W2782690739","doi":"https://doi.org/10.1109/bigdata.2017.8257984","title":"Rhea: Adaptively sampling authoritative content from social activity streams","display_name":"Rhea: Adaptively sampling authoritative content from social activity streams","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2782690739","doi":"https://doi.org/10.1109/bigdata.2017.8257984","mag":"2782690739"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8257984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8257984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","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/A5054326104","display_name":"Panagiotis Liakos","orcid":"https://orcid.org/0000-0003-4569-7801"},"institutions":[{"id":"https://openalex.org/I200777214","display_name":"National and Kapodistrian University of Athens","ror":"https://ror.org/04gnjpq42","country_code":"GR","type":"education","lineage":["https://openalex.org/I200777214"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Panagiotis Liakos","raw_affiliation_strings":["University of Athens, Athens, Greece"],"affiliations":[{"raw_affiliation_string":"University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I200777214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063868835","display_name":"Alexandrosb Ntoulas","orcid":null},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexandrosb Ntoulas","raw_affiliation_strings":["LinkedIn, Mountain View, CA"],"affiliations":[{"raw_affiliation_string":"LinkedIn, Mountain View, CA","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112128898","display_name":"Alex Delis","orcid":null},"institutions":[{"id":"https://openalex.org/I200777214","display_name":"National and Kapodistrian University of Athens","ror":"https://ror.org/04gnjpq42","country_code":"GR","type":"education","lineage":["https://openalex.org/I200777214"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Alex Delis","raw_affiliation_strings":["New York University Abu Dhabi, Abu Dhabi, U.A.E","University of Athens, Athens, Greece"],"affiliations":[{"raw_affiliation_string":"New York University Abu Dhabi, Abu Dhabi, U.A.E","institution_ids":[]},{"raw_affiliation_string":"University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I200777214"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054326104"],"corresponding_institution_ids":["https://openalex.org/I200777214"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19021368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"686","last_page":"695"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8035406470298767},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6434047818183899},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6095123291015625},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5888683199882507},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5071392059326172},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.49589475989341736},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.46696048974990845},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43547946214675903},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.413249135017395},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39360421895980835},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3805345892906189},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34736526012420654},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.2900049686431885},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.22784796357154846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8035406470298767},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6434047818183899},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6095123291015625},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5888683199882507},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5071392059326172},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.49589475989341736},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.46696048974990845},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43547946214675903},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.413249135017395},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39360421895980835},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3805345892906189},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34736526012420654},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.2900049686431885},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.22784796357154846},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8257984","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8257984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4399999976158142,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W950821216","https://openalex.org/W1845748792","https://openalex.org/W1854214752","https://openalex.org/W1966271560","https://openalex.org/W1968133322","https://openalex.org/W1975583660","https://openalex.org/W1988374254","https://openalex.org/W2025895610","https://openalex.org/W2030035054","https://openalex.org/W2037858832","https://openalex.org/W2061901927","https://openalex.org/W2062743812","https://openalex.org/W2075397336","https://openalex.org/W2080234606","https://openalex.org/W2094268994","https://openalex.org/W2112056172","https://openalex.org/W2114725120","https://openalex.org/W2119326361","https://openalex.org/W2131676173","https://openalex.org/W2132613313","https://openalex.org/W2236011370","https://openalex.org/W2296407087","https://openalex.org/W2296501108","https://openalex.org/W2404243041","https://openalex.org/W2964300898","https://openalex.org/W4213009331","https://openalex.org/W6638777778","https://openalex.org/W6679739311","https://openalex.org/W6689774210","https://openalex.org/W7071360456"],"related_works":["https://openalex.org/W2188500270","https://openalex.org/W2303858293","https://openalex.org/W2915512527","https://openalex.org/W51364034","https://openalex.org/W2793336762","https://openalex.org/W2091548507","https://openalex.org/W2368816706","https://openalex.org/W3159414774","https://openalex.org/W4385728102","https://openalex.org/W2955875337"],"abstract_inverted_index":{"Processing":[0],"the":[1,36,61,95,108,115,129],"full":[2],"activity":[3,38,72,90,130],"stream":[4,79,87],"of":[5,17,35,63,66,88,97,110,177],"a":[6,33,70,86,162],"social":[7,37,71,89,156],"network":[8],"in":[9,15,91,128,175],"real":[10],"time":[11,122],"is":[12,30,114],"oftentimes":[13],"prohibitive":[14],"terms":[16,176],"both":[18,178],"storage":[19],"and":[20,39,93,180],"computational":[21],"cost.":[22],"One":[23],"way":[24],"to":[25,31,43,103,123,136,160],"work":[26],"around":[27],"this":[28,41,57],"problem":[29,62],"take":[32],"sample":[34,42],"use":[40],"feed":[44],"into":[45],"applications":[46],"such":[47],"as":[48],"content":[49,68,96,140],"recommendation,":[50],"opinion":[51],"mining,":[52],"or":[53],"sentiment":[54],"analysis.":[55],"In":[56],"paper,":[58],"we":[59,75,133,169],"study":[60],"extracting":[64],"samples":[65,94],"authoritative":[67],"from":[69,141],"stream.":[73,131],"Specifically,":[74],"propose":[76],"an":[77],"adaptive":[78],"sampling":[80],"approach,":[81],"termed":[82],"Rhea,":[83],"that":[84,99,118,144,168],"processes":[85],"real-time":[92],"users":[98,143],"are":[100,134],"more":[101,186],"likely":[102],"provide":[104],"influential":[105],"information.":[106],"To":[107],"best":[109],"our":[111],"knowledge,":[112],"Rhea":[113,152],"first":[116],"algorithm":[117],"dynamically":[119],"adapts":[120],"over":[121],"account":[124],"for":[125],"evolving":[126],"trends":[127],"Thus,":[132],"able":[135],"capture":[137],"high":[138],"quality":[139],"emerging":[142],"contemporary":[145],"white-list":[146],"based":[147],"methods":[148,174],"ignore.":[149],"We":[150],"evaluate":[151],"using":[153],"two":[154],"popular":[155],"networks":[157],"reaching":[158],"up":[159],"half":[161],"billion":[163],"posts.":[164],"Our":[165],"results":[166],"show":[167],"significantly":[170],"outperform":[171],"previously":[172],"proposed":[173],"recall":[179],"precision,":[181],"while":[182],"also":[183],"offering":[184],"remarkably":[185],"accurate":[187],"ranking.":[188]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
