{"id":"https://openalex.org/W4213361064","doi":"https://doi.org/10.1145/3488560.3498398","title":"Friend Story Ranking with Edge-Contextual Local Graph Convolutions","display_name":"Friend Story Ranking with Edge-Contextual Local Graph Convolutions","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4213361064","doi":"https://doi.org/10.1145/3488560.3498398"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498398","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498398","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070663881","display_name":"Xianfeng Tang","orcid":"https://orcid.org/0000-0002-7955-3104"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xianfeng Tang","raw_affiliation_strings":["Amazon, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016839661","display_name":"Yozen Liu","orcid":"https://orcid.org/0000-0002-2107-504X"},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yozen Liu","raw_affiliation_strings":["Snap Inc., Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Snap Inc., Los Angeles, CA, USA","institution_ids":["https://openalex.org/I4210142583"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010444015","display_name":"Xinran He","orcid":"https://orcid.org/0000-0002-6812-518X"},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinran He","raw_affiliation_strings":["Snap Inc., Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Snap Inc., Los Angeles, CA, USA","institution_ids":["https://openalex.org/I4210142583"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011048500","display_name":"Suhang Wang","orcid":"https://orcid.org/0000-0003-3448-4878"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhang Wang","raw_affiliation_strings":["The Pennsylvania State University, State College, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, State College, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101799872","display_name":"Neil Shah","orcid":"https://orcid.org/0000-0003-3261-8430"},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neil Shah","raw_affiliation_strings":["Snap Inc., Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Snap Inc., Los Angeles, CA, USA","institution_ids":["https://openalex.org/I4210142583"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1322,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.9159808,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1007","last_page":"1015"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9994999766349792,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9749000072479248,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7789459228515625},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.6365642547607422},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5828908085823059},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5619522929191589},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.445919007062912},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.42077043652534485},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41075676679611206},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3529508709907532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3503221869468689},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.32007327675819397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7789459228515625},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.6365642547607422},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5828908085823059},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5619522929191589},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.445919007062912},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.42077043652534485},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41075676679611206},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3529508709907532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3503221869468689},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32007327675819397},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498398","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498398","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1950507725","display_name":"III: Medium: Collaborative Research: Towards Scalable and Interpretable Graph Neural Networks","funder_award_id":"1955851","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W82211948","https://openalex.org/W1492581097","https://openalex.org/W1888005072","https://openalex.org/W1979104937","https://openalex.org/W1993897382","https://openalex.org/W1994618970","https://openalex.org/W2039688703","https://openalex.org/W2063605661","https://openalex.org/W2077933964","https://openalex.org/W2119825970","https://openalex.org/W2131681506","https://openalex.org/W2133576408","https://openalex.org/W2142517301","https://openalex.org/W2154851992","https://openalex.org/W2386195190","https://openalex.org/W2393319904","https://openalex.org/W2605350416","https://openalex.org/W2614812929","https://openalex.org/W2742503211","https://openalex.org/W2743104969","https://openalex.org/W2807021761","https://openalex.org/W2809409545","https://openalex.org/W2809496930","https://openalex.org/W2891704284","https://openalex.org/W2907827821","https://openalex.org/W2914721378","https://openalex.org/W2925395532","https://openalex.org/W2950697450","https://openalex.org/W2951256120","https://openalex.org/W2962756421","https://openalex.org/W2963066159","https://openalex.org/W2991847337","https://openalex.org/W2994598354","https://openalex.org/W3048692209","https://openalex.org/W3081203761","https://openalex.org/W3093551363","https://openalex.org/W3093622219","https://openalex.org/W3093696863","https://openalex.org/W3099768174","https://openalex.org/W3100848837","https://openalex.org/W3103409210","https://openalex.org/W3104097132","https://openalex.org/W3104211877","https://openalex.org/W3104667978","https://openalex.org/W3154818219","https://openalex.org/W4288080214","https://openalex.org/W4291474301","https://openalex.org/W4298275775"],"related_works":["https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W2201908702","https://openalex.org/W4381094582","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W1977906818","https://openalex.org/W1522139108","https://openalex.org/W2353528968","https://openalex.org/W2032776242"],"abstract_inverted_index":{"Social":[0],"platforms":[1,22],"have":[2,23],"paved":[3],"the":[4,101,142,176,249],"way":[5],"in":[6,72,81,198],"creating":[7],"new,":[8],"modern":[9],"ways":[10],"for":[11,76],"users":[12,214],"to":[13,40,58,88,145],"communicate":[14],"with":[15,211],"each":[16,84],"other.":[17],"In":[18,96],"recent":[19],"years,":[20],"multiple":[21,195],"introduced":[24],"''Stories''":[25],"features,":[26],"which":[27,157],"enable":[28],"broadcasting":[29],"of":[30,104,178,213,217,219,251],"ephemeral":[31],"multimedia":[32],"content.":[33],"Specifically,":[34],"''Friend":[35],"Stories,''":[36],"or":[37,134,137],"Stories":[38,75],"meant":[39],"be":[41],"consumed":[42],"by":[43,55,186,229,236],"one's":[44],"close":[45],"friends,":[46],"are":[47,66,125],"a":[48,77,109,119],"popular":[49],"feature,":[50],"promoting":[51],"significant":[52],"user-user":[53],"interactions":[54],"allowing":[56],"people":[57],"see":[59],"(visually)":[60],"what":[61],"their":[62],"friends":[63,87],"and":[64,91,168,170,188,193,215,231,238,245],"family":[65],"up":[67],"to.":[68],"A":[69],"key":[70],"challenge":[71],"surfacing":[73],"Friend":[74,105],"given":[78],"user,":[79],"is":[80,118,144],"ranking":[82,121],"over":[83,127,190,227],"viewing":[85],"user's":[86],"efficiently":[89],"prioritize":[90],"route":[92],"limited":[93],"user":[94],"attention.":[95],"this":[97],"work,":[98],"we":[99],"explore":[100],"novel":[102],"problem":[103,117],"Story":[106],"Ranking":[107],"from":[108,221],"graph":[110,161,179],"representation":[111],"learning":[112],"perspective.":[113],"More":[114],"generally,":[115],"our":[116],"link":[120,138],"task,":[122],"where":[123,141],"inferences":[124,147],"made":[126],"existing":[128],"links":[129,220],"(relations),":[130],"unlike":[131],"common":[132],"node":[133],"graph-based":[135],"tasks,":[136,140],"prediction":[139],"goal":[143],"make":[146],"about":[148],"non-existing":[149],"links.":[150],"We":[151,203],"propose":[152],"ELR,":[153],"an":[154],"edge-contextual":[155],"approach":[156],"carefully":[158],"considers":[159],"local":[160,165,199],"structure,":[162],"differences":[163],"between":[164],"edge":[166,172,196],"types":[167,197],"directionality,":[169],"rich":[171],"attributes,":[173],"building":[174],"on":[175,206],"backbone":[177],"convolutions.":[180],"ELR":[181,205,223],"handles":[182],"social":[183],"sparsity":[184],"challenges":[185],"considering":[187],"attending":[189],"neighboring":[191],"nodes,":[192],"incorporating":[194],"surrounding":[200],"egonet":[201],"structures.":[202],"validate":[204],"two":[207],"large":[208],"country-level":[209],"datasets":[210],"millions":[212,218],"tens":[216],"Snapchat.":[222],"shows":[224],"superior":[225],"performance":[226],"alternatives":[228],"8%":[230],"5%":[232],"error":[233],"reduction":[234],"measured":[235],"MSE":[237],"MAE":[239],"correspondingly.":[240],"Further":[241],"generality,":[242],"data":[243],"efficiency":[244],"ablation":[246],"experiments":[247],"confirm":[248],"advantages":[250],"ELR.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}