{"id":"https://openalex.org/W4409670770","doi":"https://doi.org/10.1145/3696410.3714650","title":"Domain-Informed Negative Sampling Strategies for Dynamic Graph Embedding in Meme Stock-Related Social Networks","display_name":"Domain-Informed Negative Sampling Strategies for Dynamic Graph Embedding in Meme Stock-Related Social Networks","publication_year":2025,"publication_date":"2025-04-22","ids":{"openalex":"https://openalex.org/W4409670770","doi":"https://doi.org/10.1145/3696410.3714650"},"language":"en","primary_location":{"id":"doi:10.1145/3696410.3714650","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714650","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714650","source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714650","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110976362","display_name":"Yunming Hui","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Yunming Hui","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"raw_orcid":"https://orcid.org/0009-0004-2908-9042","affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061494936","display_name":"Inez Maria Zwetsloot","orcid":"https://orcid.org/0000-0002-6144-4188"},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Inez Maria Zwetsloot","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-6144-4188","affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000536164","display_name":"Simon Trimborn","orcid":"https://orcid.org/0000-0003-3745-4164"},"institutions":[{"id":"https://openalex.org/I198488067","display_name":"Tinbergen Institute","ror":"https://ror.org/054xxtt73","country_code":"NL","type":"education","lineage":["https://openalex.org/I198488067"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Simon Trimborn","raw_affiliation_strings":["Amsterdam School of Economics, University of Amsterdam, Amsterdam, Netherlands and Tinbergen Institute, Amsterdam, Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-3745-4164","affiliations":[{"raw_affiliation_string":"Amsterdam School of Economics, University of Amsterdam, Amsterdam, Netherlands and Tinbergen Institute, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I198488067","https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075331928","display_name":"Stevan Rudinac","orcid":"https://orcid.org/0000-0003-1904-8736"},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Stevan Rudinac","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"raw_orcid":"https://orcid.org/0000-0003-1904-8736","affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.5787,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.96682171,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"518","last_page":"529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9961000084877014,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9884999990463257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6162729859352112},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5280336141586304},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.46781396865844727},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.45782551169395447},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44698476791381836},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4309404492378235},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.4149476885795593},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31634968519210815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22769147157669067},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09863266348838806},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08532688021659851}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6162729859352112},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5280336141586304},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.46781396865844727},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.45782551169395447},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44698476791381836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4309404492378235},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.4149476885795593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31634968519210815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22769147157669067},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09863266348838806},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08532688021659851},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3696410.3714650","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714650","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714650","source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},{"id":"pmh:oai:dare.uva.nl:openaire/a624418c-47c5-431f-a986-373b65ae7ffc","is_oa":false,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/domaininformed-negative-sampling-strategies-for-dynamic-graph-embedding-in-meme-stockrelated-social-networks(a624418c-47c5-431f-a986-373b65ae7ffc).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Hui, Y, Zwetsloot, I M, Trimborn, S & Rudinac, S 2025, Domain-Informed Negative Sampling Strategies for Dynamic Graph Embedding in Meme Stock-Related Social Networks. in WWW '25 : Proceedings of the ACM Web Conference 2025 : April 28-May 2, 2025, Sydney, NSW, Australia. Association for Computing Machinery, New York, NY, pp. 518-529, 34th ACM Web Conference, WWW 2025, Sydney, Australia, 28/04/25. https://doi.org/10.1145/3696410.3714650","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1145/3696410.3714650","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714650","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714650","source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409670770.pdf","grobid_xml":"https://content.openalex.org/works/W4409670770.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1534704610","https://openalex.org/W1544435011","https://openalex.org/W1995881620","https://openalex.org/W2027135291","https://openalex.org/W2073415627","https://openalex.org/W2076954624","https://openalex.org/W2096451472","https://openalex.org/W2118978333","https://openalex.org/W2767922951","https://openalex.org/W2981405661","https://openalex.org/W3026640598","https://openalex.org/W3045255111","https://openalex.org/W3080456792","https://openalex.org/W3105708681","https://openalex.org/W3109841242","https://openalex.org/W3122069311","https://openalex.org/W3136378589","https://openalex.org/W3153858161","https://openalex.org/W3166605255","https://openalex.org/W3187811656","https://openalex.org/W3199464337","https://openalex.org/W3209485964","https://openalex.org/W3214753197","https://openalex.org/W4220822815","https://openalex.org/W4283205897","https://openalex.org/W4286750969","https://openalex.org/W4292808934","https://openalex.org/W4360887650","https://openalex.org/W4367046696","https://openalex.org/W4386730515","https://openalex.org/W4387848566","https://openalex.org/W4391904661","https://openalex.org/W4391915043","https://openalex.org/W7045313712"],"related_works":["https://openalex.org/W3206528106","https://openalex.org/W3036264823","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W2088740331","https://openalex.org/W3038102983","https://openalex.org/W2950907416","https://openalex.org/W1559483280","https://openalex.org/W2082479932","https://openalex.org/W2932872266"],"abstract_inverted_index":{"Social":[0],"network":[1,96],"platforms":[2],"like":[3],"Reddit":[4],"are":[5,12,19,91,128],"increasingly":[6],"impacting":[7],"real-world":[8],"economics.":[9],"Meme":[10],"stocks":[11],"a":[13,110],"recent":[14],"phenomena":[15],"where":[16],"price":[17,100],"movements":[18],"driven":[20],"by":[21],"retail":[22],"investors":[23],"organizing":[24],"themselves":[25],"via":[26],"social":[27,34,146,159,179,204],"networks.":[28,46,147,160],"To":[29,161],"study":[30],"the":[31,39,87,95,139,150,173,188],"impact":[32],"of":[33,126,154,175],"networks":[35,180,205],"on":[36,172],"meme":[37,50,98,144,177,202],"stocks,":[38],"first":[40],"step":[41],"is":[42,61,77],"to":[43,55,79,97,207],"analyze":[44],"these":[45],"Going":[47],"forward,":[48],"predicting":[49],"stocks'":[51],"returns":[52],"would":[53],"require":[54],"predict":[56,80],"dynamic":[57,115,132],"interactions":[58],"first.":[59],"This":[60,148],"different":[62],"from":[63],"conventional":[64,131],"link":[65,133],"prediction,":[66],"frequently":[67],"applied":[68],"in":[69,143,157],"e.g.":[70],"recommendation":[71],"systems.":[72],"For":[73],"this":[74,163],"task,":[75],"it":[76],"essential":[78],"more":[81],"complex":[82],"interaction":[83],"dynamics,":[84],"such":[85,158],"as":[86,109],"exact":[88],"timing.":[89],"These":[90],"crucial":[92],"for":[93,113,130],"linking":[94],"stock":[99],"movements.":[101],"Dynamic":[102],"graph":[103],"embedding":[104],"(DGE)":[105],"has":[106],"recently":[107],"emerged":[108],"promising":[111],"approach":[112],"modeling":[114],"graph-structured":[116],"data.":[117],"However,":[118],"current":[119],"negative":[120,168,190],"sampling":[121,169,191],"strategies,":[122],"an":[123],"important":[124],"component":[125],"DGE,":[127],"designed":[129],"prediction":[134],"and":[135,152,181,196],"do":[136],"not":[137],"capture":[138],"specific":[140],"patterns":[141],"present":[142],"stock-related":[145,178,203],"limits":[149],"training":[151],"evaluation":[153],"DGE":[155,198],"models":[156,199],"overcome":[162],"drawback,":[164],"we":[165],"propose":[166],"novel":[167],"strategies":[170,192],"based":[171],"analysis":[174],"real":[176],"financial":[182],"knowledge.":[183],"Our":[184],"experiments":[185],"show":[186],"that":[187],"proposed":[189],"can":[193],"better":[194],"evaluate":[195],"train":[197],"targeted":[200],"at":[201],"compared":[206],"existing":[208],"baselines.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
