{"id":"https://openalex.org/W4220707454","doi":"https://doi.org/10.1145/3524105","title":"A Survey of Sampling Method for Social Media Embeddedness Relationship","display_name":"A Survey of Sampling Method for Social Media Embeddedness Relationship","publication_year":2022,"publication_date":"2022-03-30","ids":{"openalex":"https://openalex.org/W4220707454","doi":"https://doi.org/10.1145/3524105"},"language":"en","primary_location":{"id":"doi:10.1145/3524105","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524105","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"type":"review","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/A5055183642","display_name":"Yingan Cui","orcid":"https://orcid.org/0000-0003-2031-7315"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingan Cui","raw_affiliation_strings":["Xi'an University of Technology, Shaanxi Province, China"],"raw_orcid":"https://orcid.org/0000-0003-2031-7315","affiliations":[{"raw_affiliation_string":"Xi'an University of Technology, Shaanxi Province, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102904375","display_name":"Li Xue","orcid":"https://orcid.org/0000-0002-6229-2390"},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Li","raw_affiliation_strings":["Shaanxi Normal of University, Shaanxi Province, China"],"raw_orcid":"https://orcid.org/0000-0002-6229-2390","affiliations":[{"raw_affiliation_string":"Shaanxi Normal of University, Shaanxi Province, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046113804","display_name":"Junhuai Li","orcid":"https://orcid.org/0000-0001-5483-5175"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhuai Li","raw_affiliation_strings":["Xi'an University of Technology, Shaanxi Province, China"],"raw_orcid":"https://orcid.org/0000-0001-5483-5175","affiliations":[{"raw_affiliation_string":"Xi'an University of Technology, Shaanxi Province, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069263111","display_name":"Huaijun Wang","orcid":"https://orcid.org/0000-0002-2933-6566"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaijun Wang","raw_affiliation_strings":["Xi'an University of Technology, Shaanxi Province, China"],"raw_orcid":"https://orcid.org/0000-0002-2933-6566","affiliations":[{"raw_affiliation_string":"Xi'an University of Technology, Shaanxi Province, China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaogang Chen","orcid":"https://orcid.org/0000-0003-2345-506X"},"institutions":[{"id":"https://openalex.org/I204831749","display_name":"Southwestern University of Finance and Economics","ror":"https://ror.org/04ewct822","country_code":"CN","type":"education","lineage":["https://openalex.org/I204831749"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaogang Chen","raw_affiliation_strings":["Southwestern University of Finance and Economics, Sichuan Province, China"],"raw_orcid":"https://orcid.org/0000-0003-2345-506X","affiliations":[{"raw_affiliation_string":"Southwestern University of Finance and Economics, Sichuan Province, China","institution_ids":["https://openalex.org/I204831749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5026,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.81646841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"55","issue":"4","first_page":"1","last_page":"39"},"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9968000054359436,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9891999959945679,"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/computer-science","display_name":"Computer science","score":0.7745015621185303},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7374900579452515},{"id":"https://openalex.org/keywords/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.5761274695396423},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5686343312263489},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.5343135595321655},{"id":"https://openalex.org/keywords/experience-sampling-method","display_name":"Experience sampling method","score":0.4848969578742981},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4738776385784149},{"id":"https://openalex.org/keywords/betweenness-centrality","display_name":"Betweenness centrality","score":0.46025100350379944},{"id":"https://openalex.org/keywords/embeddedness","display_name":"Embeddedness","score":0.4574602544307709},{"id":"https://openalex.org/keywords/cluster-sampling","display_name":"Cluster sampling","score":0.4536917805671692},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.44541552662849426},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4329601526260376},{"id":"https://openalex.org/keywords/survey-sampling","display_name":"Survey sampling","score":0.42126697301864624},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.38054603338241577},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3231718838214874},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10934180021286011},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09353896975517273},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08450973033905029}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7745015621185303},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7374900579452515},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.5761274695396423},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5686343312263489},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.5343135595321655},{"id":"https://openalex.org/C65499552","wikidata":"https://www.wikidata.org/wiki/Q5421061","display_name":"Experience sampling method","level":2,"score":0.4848969578742981},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4738776385784149},{"id":"https://openalex.org/C117045392","wikidata":"https://www.wikidata.org/wiki/Q4899215","display_name":"Betweenness centrality","level":3,"score":0.46025100350379944},{"id":"https://openalex.org/C63063934","wikidata":"https://www.wikidata.org/wiki/Q1079747","display_name":"Embeddedness","level":2,"score":0.4574602544307709},{"id":"https://openalex.org/C183380357","wikidata":"https://www.wikidata.org/wiki/Q1776598","display_name":"Cluster sampling","level":3,"score":0.4536917805671692},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.44541552662849426},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4329601526260376},{"id":"https://openalex.org/C5733905","wikidata":"https://www.wikidata.org/wiki/Q10744315","display_name":"Survey sampling","level":3,"score":0.42126697301864624},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.38054603338241577},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3231718838214874},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10934180021286011},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09353896975517273},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08450973033905029},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3524105","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524105","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"awards":[{"id":"https://openalex.org/G3134235651","display_name":"\u57fa\u4e8e\u8fd0\u52a8\u751f\u7269\u529b\u5b66\u7684\u4eba\u4f53\u52a8\u4f5c\u6a21\u5f0f\u63cf\u8ff0\u4e0e\u8bc6\u522b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971347","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6915721211","display_name":null,"funder_award_id":"201803090","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":108,"referenced_works":["https://openalex.org/W133826493","https://openalex.org/W813892931","https://openalex.org/W1524314678","https://openalex.org/W1558755690","https://openalex.org/W1591516103","https://openalex.org/W1964062850","https://openalex.org/W1966342313","https://openalex.org/W1973846084","https://openalex.org/W1985688105","https://openalex.org/W1989054110","https://openalex.org/W1989524890","https://openalex.org/W1990017756","https://openalex.org/W1993324688","https://openalex.org/W1994356260","https://openalex.org/W2016589434","https://openalex.org/W2017319780","https://openalex.org/W2029130073","https://openalex.org/W2030644393","https://openalex.org/W2042359627","https://openalex.org/W2045025184","https://openalex.org/W2049297549","https://openalex.org/W2052618365","https://openalex.org/W2056824075","https://openalex.org/W2058446729","https://openalex.org/W2060173274","https://openalex.org/W2065222371","https://openalex.org/W2069353545","https://openalex.org/W2070722739","https://openalex.org/W2085962141","https://openalex.org/W2086182666","https://openalex.org/W2087247903","https://openalex.org/W2102862543","https://openalex.org/W2106315062","https://openalex.org/W2115022330","https://openalex.org/W2118910235","https://openalex.org/W2124450885","https://openalex.org/W2125525771","https://openalex.org/W2127503167","https://openalex.org/W2127931346","https://openalex.org/W2135658909","https://openalex.org/W2135832103","https://openalex.org/W2137135938","https://openalex.org/W2139534421","https://openalex.org/W2142645441","https://openalex.org/W2142809881","https://openalex.org/W2146008005","https://openalex.org/W2146458746","https://openalex.org/W2147256592","https://openalex.org/W2148301044","https://openalex.org/W2148606196","https://openalex.org/W2152046791","https://openalex.org/W2152710063","https://openalex.org/W2153062527","https://openalex.org/W2153204928","https://openalex.org/W2157305458","https://openalex.org/W2157747946","https://openalex.org/W2161455936","https://openalex.org/W2163495823","https://openalex.org/W2164713644","https://openalex.org/W2167011266","https://openalex.org/W2168380307","https://openalex.org/W2195224909","https://openalex.org/W2222326741","https://openalex.org/W2286079480","https://openalex.org/W2335708241","https://openalex.org/W2477521807","https://openalex.org/W2511599668","https://openalex.org/W2513806786","https://openalex.org/W2520512868","https://openalex.org/W2560112275","https://openalex.org/W2579645957","https://openalex.org/W2582561810","https://openalex.org/W2593265540","https://openalex.org/W2593889720","https://openalex.org/W2612872092","https://openalex.org/W2620264943","https://openalex.org/W2621291094","https://openalex.org/W2737819065","https://openalex.org/W2750533795","https://openalex.org/W2756668117","https://openalex.org/W2761716478","https://openalex.org/W2761768700","https://openalex.org/W2762022221","https://openalex.org/W2782087530","https://openalex.org/W2792302213","https://openalex.org/W2802870214","https://openalex.org/W2807791198","https://openalex.org/W2808154726","https://openalex.org/W2878895971","https://openalex.org/W2885426747","https://openalex.org/W2907685836","https://openalex.org/W2907841103","https://openalex.org/W2922398414","https://openalex.org/W2963224980","https://openalex.org/W2963512530","https://openalex.org/W2964019651","https://openalex.org/W2998009705","https://openalex.org/W3010799329","https://openalex.org/W3090080827","https://openalex.org/W3092277776","https://openalex.org/W3100007618","https://openalex.org/W3102208898","https://openalex.org/W3122605581","https://openalex.org/W3124659759","https://openalex.org/W3206333935","https://openalex.org/W4243349358","https://openalex.org/W6744732525","https://openalex.org/W6747581376"],"related_works":["https://openalex.org/W3159631231","https://openalex.org/W2356738361","https://openalex.org/W1516497519","https://openalex.org/W2103926897","https://openalex.org/W4306248409","https://openalex.org/W2012724202","https://openalex.org/W3006871705","https://openalex.org/W2062728131","https://openalex.org/W2376216667","https://openalex.org/W2416722981"],"abstract_inverted_index":{"Social":[0],"media":[1,35,87],"embeddedness":[2,36],"relationships":[3,37],"consist":[4],"of":[5,19,28,53,71,133,171],"online":[6],"social":[7,34,86],"networks":[8,31,101],"formed":[9],"by":[10,33],"self-organized":[11],"individual":[12],"actors":[13],"and":[14,26,66,105,107,124,148,150,169,175],"significantly":[15],"affect":[16,120],"many":[17],"aspects":[18],"our":[20],"lives.":[21],"Since":[22],"the":[23,75,103,109,117,121,130,137,146,162,167],"high":[24],"cost":[25],"inefficiency":[27],"using":[29,83],"population":[30],"generated":[32],"to":[38],"study":[39],"practical":[40],"issues,":[41],"sampling":[42,61,81,95,114,122,134,152,173],"techniques":[43],"have":[44],"become":[45],"increasingly":[46],"important":[47],"than":[48],"ever.":[49],"Our":[50],"work":[51],"consists":[52],"three":[54],"parts.":[55],"We":[56],"first":[57],"comprehensively":[58],"analyze":[59],"current":[60,151,172],"selection":[62],"methods,":[63],"evaluation":[64,67],"indexes,":[65],"methods":[68,96,153,174],"in":[69],"terms":[70],"technological":[72],"evolution.":[73],"In":[74,161],"second":[76],"part,":[77,164],"we":[78,165],"systematically":[79],"conduct":[80],"tests":[82,127],"representative":[84],"large-scale":[85],"datasets.":[88],"The":[89],"test":[90],"results":[91],"indicate":[92],"that":[93,129],"unequal-probability":[94],"can":[97],"construct":[98],"similar":[99],"sample":[100,156],"at":[102,116],"macroscale":[104],"microscale":[106],"outperform":[108],"equal-probability":[110],"methods.":[111],"However,":[112],"non-negligible":[113],"errors":[115,135],"mesoscale":[118],"seriously":[119],"reliability":[123],"validity.":[125],"MANOVA":[126],"show":[128],"direct":[131],"cause":[132],"is":[136],"low":[138],"in-degree":[139],"nodes":[140],"with":[141],"medium-high":[142],"betweenness":[143],"located":[144],"between":[145],"core":[147],"periphery,":[149],"cannot":[154],"accurately":[155],"such":[157],"complex":[158],"interconnected":[159],"structures.":[160],"third":[163],"summarize":[166],"pros":[168],"cons":[170],"provide":[176],"suggestions":[177],"for":[178],"future":[179],"work.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}