{"id":"https://openalex.org/W4384895507","doi":"https://doi.org/10.1145/3539618.3592087","title":"Where Does Your News Come From? Predicting Information Pathways in Social Media","display_name":"Where Does Your News Come From? Predicting Information Pathways in Social Media","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384895507","doi":"https://doi.org/10.1145/3539618.3592087"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3592087","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539618.3592087","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592087","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 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/10.1145/3539618.3592087","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023181512","display_name":"Alexander K. Taylor","orcid":"https://orcid.org/0000-0002-0251-2961"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander K. Taylor","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0251-2961","affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nuan Wen","orcid":"https://orcid.org/0009-0004-4772-859X"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nuan Wen","raw_affiliation_strings":["University Southern California, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0009-0004-4772-859X","affiliations":[{"raw_affiliation_string":"University Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103215788","display_name":"P.C. Kung","orcid":"https://orcid.org/0009-0007-0780-8335"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Po-Nien Kung","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0009-0007-0780-8335","affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102986685","display_name":"Jiaao Chen","orcid":"https://orcid.org/0009-0004-8425-2893"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaao Chen","raw_affiliation_strings":["Georgia Tech, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0009-0004-8425-2893","affiliations":[{"raw_affiliation_string":"Georgia Tech, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112963330","display_name":"Violet Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Violet Peng","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8509-6595","affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100392089","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8180-2886"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8180-2886","affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7587,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.83663834,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2511","last_page":"2515"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9979000091552734,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9915000200271606,"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":0.7856979370117188},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6483985185623169},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5802270770072937},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5624083876609802},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5413761734962463},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4817242920398712},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4623172879219055},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.42221590876579285},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4181445837020874},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3475131094455719},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3200330138206482},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24936923384666443}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7856979370117188},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6483985185623169},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5802270770072937},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5624083876609802},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5413761734962463},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4817242920398712},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4623172879219055},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.42221590876579285},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4181445837020874},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3475131094455719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3200330138206482},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24936923384666443},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539618.3592087","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539618.3592087","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592087","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 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3539618.3592087","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539618.3592087","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539618.3592087","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 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.46000000834465027}],"awards":[{"id":"https://openalex.org/G1523888516","display_name":null,"funder_award_id":"FA9550-","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"},{"id":"https://openalex.org/G3367813468","display_name":null,"funder_award_id":"FA9550-22-1-0380","funder_id":"https://openalex.org/F4320333591","funder_display_name":"Multidisciplinary University Research Initiative"},{"id":"https://openalex.org/G6048779419","display_name":null,"funder_award_id":"FA9550-22-1-0380","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384895507.pdf","grobid_xml":"https://content.openalex.org/works/W4384895507.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W346343780","https://openalex.org/W1499517307","https://openalex.org/W2095498219","https://openalex.org/W2767940852","https://openalex.org/W2768859421","https://openalex.org/W2913350752","https://openalex.org/W2964110616","https://openalex.org/W2997431870","https://openalex.org/W3004621088","https://openalex.org/W3026640598","https://openalex.org/W3028571922","https://openalex.org/W3099275829","https://openalex.org/W3166148088","https://openalex.org/W3193989162","https://openalex.org/W3201524732","https://openalex.org/W4205374600","https://openalex.org/W4283206413","https://openalex.org/W6600728650"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2979236518","https://openalex.org/W2013343313","https://openalex.org/W2755954602"],"abstract_inverted_index":{"As":[0],"social":[1,29],"networks":[2],"become":[3],"further":[4],"entrenched":[5],"in":[6,45],"modern":[7],"society,":[8],"it":[9],"becomes":[10],"increasingly":[11],"important":[12,116],"to":[13],"understand":[14],"and":[15,92,95,117,147,173],"predict":[16],"how":[17],"information":[18,32,73,101,150],"(e.g.,":[19],"news":[20,90],"coverage":[21],"of":[22,38,41,62,100,181],"a":[23,50,63,67,166,176,194],"given":[24,64],"event)":[25],"is":[26,114],"propagated":[27],"across":[28,103],"media":[30,104],"(i.e.,":[31],"pathway),":[33],"which":[34,57],"helps":[35],"the":[36,39,59,72,98,132,136,154,160],"understandings":[37],"impact":[40],"real-world":[42],"information.":[43],"Thus,":[44],"this":[46,113],"paper,":[47],"we":[48,81,163],"propose":[49],"novel":[51,167],"task,":[52,162],"Information":[53],"Pathway":[54],"Prediction":[55],"(IPP),":[56],"depicts":[58],"propagation":[60,151],"paths":[61],"passage":[65],"as":[66],"community":[68,77,108],"tree":[69],"(rooted":[70],"at":[71,131],"source)":[74],"on":[75,106,121,135],"constructed":[76],"interaction":[78],"graphs":[79],"where":[80],"first":[82],"aggregate":[83],"individual":[84,139],"users":[85,140],"into":[86],"communities":[87],"formed":[88],"around":[89],"sources":[91],"influential":[93],"users,":[94],"then":[96],"elucidate":[97],"patterns":[99],"dissemination":[102],"based":[105],"such":[107],"nodes.":[109],"We":[110],"argue":[111],"that":[112,186],"an":[115],"useful":[118],"task":[119],"because,":[120],"one":[122],"hand,":[123,138],"community-level":[124,149],"interactions":[125],"offer":[126],"more":[127],"stability":[128],"than":[129],"those":[130],"user":[133],"level;":[134],"other":[137],"are":[141],"often":[142],"influenced":[143],"by":[144,193],"their":[145],"community,":[146],"modeling":[148],"will":[152],"help":[153],"traditional":[155],"link-prediction":[156],"problem.":[157],"To":[158],"tackle":[159],"IPP":[161],"introduce":[164],"Lightning,":[165],"content-aware":[168],"link":[169,190],"prediction":[170,191],"GNN":[171],"model":[172],"demonstrate":[174],"using":[175],"large":[177],"Twitter":[178],"dataset":[179],"consisting":[180],"all":[182],"COVID":[183],"related":[184],"tweets":[185],"Lightning":[187],"outperforms":[188],"state-of-the-art":[189],"baselines":[192],"significant":[195],"margin.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}