{"id":"https://openalex.org/W3174234990","doi":"https://doi.org/10.1109/tkde.2022.3174206","title":"Incomplete Gamma Integrals for Deep Cascade Prediction Using Content, Network, and Exogenous Signals","display_name":"Incomplete Gamma Integrals for Deep Cascade Prediction Using Content, Network, and Exogenous Signals","publication_year":2022,"publication_date":"2022-08-19","ids":{"openalex":"https://openalex.org/W3174234990","doi":"https://doi.org/10.1109/tkde.2022.3174206","mag":"3174234990"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3174206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3174206","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5023507685","display_name":"Subhabrata Dutta","orcid":"https://orcid.org/0000-0002-0730-0685"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Subhabrata Dutta","raw_affiliation_strings":["Department CSE, Jadavpur University, Kolkata, West Bengal, India"],"affiliations":[{"raw_affiliation_string":"Department CSE, Jadavpur University, Kolkata, West Bengal, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086690984","display_name":"Shravika Mittal","orcid":"https://orcid.org/0000-0002-4888-7996"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shravika Mittal","raw_affiliation_strings":["Department CSE, Jadavpur University, Kolkata, West Bengal, India","Adobe, India"],"affiliations":[{"raw_affiliation_string":"Department CSE, Jadavpur University, Kolkata, West Bengal, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"Adobe, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052810907","display_name":"Dipankar Das","orcid":"https://orcid.org/0000-0002-8110-9344"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dipankar Das","raw_affiliation_strings":["Department CSE, Jadavpur University, Kolkata, West Bengal, India"],"affiliations":[{"raw_affiliation_string":"Department CSE, Jadavpur University, Kolkata, West Bengal, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101457009","display_name":"Soumen Chakrabarti","orcid":"https://orcid.org/0000-0002-9419-7486"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Soumen Chakrabarti","raw_affiliation_strings":["Department of CSE, IIT Bombay, Mumbai, Maharashtra, India"],"affiliations":[{"raw_affiliation_string":"Department of CSE, IIT Bombay, Mumbai, Maharashtra, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046521217","display_name":"Tanmoy Chakraborty","orcid":"https://orcid.org/0000-0002-0210-0369"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanmoy Chakraborty","raw_affiliation_strings":["Department of CSE, IIIT Delhi, New Delhi, Delhi, India"],"affiliations":[{"raw_affiliation_string":"Department of CSE, IIIT Delhi, New Delhi, Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5023507685"],"corresponding_institution_ids":["https://openalex.org/I170979836"],"apc_list":null,"apc_paid":null,"fwci":0.1217,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36374313,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"35","issue":"6","first_page":"5991","last_page":"6002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9988999962806702,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/cascade","display_name":"Cascade","score":0.9114197492599487},{"id":"https://openalex.org/keywords/information-cascade","display_name":"Information cascade","score":0.6698192954063416},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6597034335136414},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5502731800079346},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5289632678031921},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46401605010032654},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4301929473876953},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.41753631830215454},{"id":"https://openalex.org/keywords/time-point","display_name":"Time point","score":0.4175300598144531},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3621402680873871},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.322548508644104},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2624523639678955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2246817946434021},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2151661515235901},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12070789933204651}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.9114197492599487},{"id":"https://openalex.org/C27286358","wikidata":"https://www.wikidata.org/wiki/Q6031027","display_name":"Information cascade","level":2,"score":0.6698192954063416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6597034335136414},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5502731800079346},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5289632678031921},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46401605010032654},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4301929473876953},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.41753631830215454},{"id":"https://openalex.org/C2779466056","wikidata":"https://www.wikidata.org/wiki/Q107630651","display_name":"Time point","level":2,"score":0.4175300598144531},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3621402680873871},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.322548508644104},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2624523639678955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2246817946434021},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2151661515235901},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12070789933204651},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3174206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3174206","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1508765177","https://openalex.org/W1572718941","https://openalex.org/W1780764807","https://openalex.org/W1954020979","https://openalex.org/W1967579779","https://openalex.org/W1979603873","https://openalex.org/W1996263819","https://openalex.org/W2000139610","https://openalex.org/W2042034885","https://openalex.org/W2052817812","https://openalex.org/W2061887386","https://openalex.org/W2064675550","https://openalex.org/W2064851412","https://openalex.org/W2080290417","https://openalex.org/W2109603058","https://openalex.org/W2117620267","https://openalex.org/W2136006067","https://openalex.org/W2147453867","https://openalex.org/W2153579005","https://openalex.org/W2170826378","https://openalex.org/W2251523416","https://openalex.org/W2265862919","https://openalex.org/W2398526644","https://openalex.org/W2491133297","https://openalex.org/W2510535358","https://openalex.org/W2551441958","https://openalex.org/W2584419678","https://openalex.org/W2740189214","https://openalex.org/W2767220239","https://openalex.org/W2788974574","https://openalex.org/W2795931350","https://openalex.org/W2801473415","https://openalex.org/W2808434001","https://openalex.org/W2885998864","https://openalex.org/W2905759590","https://openalex.org/W2907927214","https://openalex.org/W2949377321","https://openalex.org/W2962817261","https://openalex.org/W2963493749","https://openalex.org/W2964232927","https://openalex.org/W2970897180","https://openalex.org/W2970945590","https://openalex.org/W2971343405","https://openalex.org/W2984771190","https://openalex.org/W2997431870","https://openalex.org/W3001111845","https://openalex.org/W3008000519","https://openalex.org/W3028825970","https://openalex.org/W3047396455","https://openalex.org/W3081101222","https://openalex.org/W3094405327","https://openalex.org/W3101614988","https://openalex.org/W3104075975","https://openalex.org/W3104250540","https://openalex.org/W3104987177","https://openalex.org/W3112984234","https://openalex.org/W3122471732","https://openalex.org/W4298854966","https://openalex.org/W4385245566","https://openalex.org/W6731714541","https://openalex.org/W6757083290","https://openalex.org/W6762922688","https://openalex.org/W6762981976","https://openalex.org/W6766581138","https://openalex.org/W7015881123"],"related_works":["https://openalex.org/W4379925025","https://openalex.org/W2038891404","https://openalex.org/W3104987177","https://openalex.org/W2810784123","https://openalex.org/W3041929574","https://openalex.org/W2990751567","https://openalex.org/W4200012112","https://openalex.org/W4385988053","https://openalex.org/W4292369391","https://openalex.org/W2067425759"],"abstract_inverted_index":{"The":[0,186],"behavior":[1],"of":[2,33,60,92,107,127,143,171,207,226,234],"information":[3],"cascades":[4,209],"(such":[5],"as":[6,123],"retweets)":[7],"has":[8,28],"been":[9,19,50],"modeled":[10],"extensively.":[11],"While":[12],"point":[13],"process-based":[14],"generative":[15],"models":[16],"have":[17,48],"long":[18],"in":[20,44,224,236],"use":[21],"for":[22],"estimating":[23],"cascade":[24,45,62,68,120,173,184,251],"growths,":[25],"deep":[26,131],"learning":[27],"greatly":[29],"enhanced":[30],"the":[31,58,61,75,90,93,104,108,144,169,172,183,218],"integration":[32],"diverse":[34,200],"features":[35,140],"and":[36,103,147,199,231,243],"signals.":[37],"We":[38],"observe":[39],"two":[40],"significant":[41],"temporal":[42],"signals":[43,133,159],"data":[46],"that":[47,74],"not":[49],"reported":[51],"or":[52],"exploited":[53],"to":[54,66,98,112,181],"our":[55,155],"knowledge.":[56],"First,":[57],"popularity":[59],"root":[63,94,145],"is":[64,177],"known":[65],"influence":[67,132],"size":[69,106],"strongly;":[70],"but":[71],"we":[72,83,115],"find":[73,84],"effect":[76],"falls":[77],"off":[78],"rapidly":[79],"with":[80,211,221],"time.":[81],"Second,":[82],"a":[85,99,118,124,161,204,232],"measurable":[86],"positive":[87],"correlation":[88,230],"between":[89],"novelty":[91],"content":[95,135],"(with":[96],"respect":[97],"streaming":[100],"external":[101],"corpus)":[102],"relative":[105],"resulting":[109],"cascade.":[110],"Responding":[111],"these":[113,158],"observations,":[114],"propose":[116],"<monospace>GammaCas</monospace>,":[117],"new":[119],"growth":[121],"model":[122,156],"parametric":[125],"function":[126],"time,":[128],"which":[129,176],"combines":[130],"from":[134],"(e.g.,":[136,141,151],"tweet":[137],"text),":[138],"network":[139,187],"followers":[142],"user),":[146],"exogenous":[148],"event":[149],"sources":[150],"online":[152,213],"news).":[153],"Specifically,":[154],"processes":[157],"through":[160],"customized":[162],"recurrent":[163],"network,":[164],"whose":[165],"states":[166],"then":[167],"provide":[168],"parameters":[170,188],"rate":[174],"function,":[175],"integrated":[178],"over":[179],"time":[180],"predict":[182],"size.":[185],"are":[189],"trained":[190],"end-to-end":[191],"using":[192],"observed":[193],"cascades.":[194],"<monospace>GammaCas</monospace>":[195],"outperforms":[196],"seven":[197],"recent":[198],"baselines":[201],"significantly":[202],"on":[203],"large-scale":[205],"dataset":[206],"retweet":[208,250],"coupled":[210],"time-aligned":[212],"news":[214],"&#x2014;":[215],"it":[216],"beats":[217],"best":[219],"baseline":[220],"18.98&#x0025;":[222],"increase":[223],"terms":[225],"Kendall&#x0027;s":[227],"<inline-formula><tex-math":[228],"notation=\"LaTeX\">$\\tau$</tex-math></inline-formula>":[229],"reduction":[233],"19.2":[235],"Mean":[237],"Absolute":[238],"Percentage":[239],"Error.":[240],"Extensive":[241],"ablation":[242],"case":[244],"studies":[245],"unearth":[246],"interesting":[247],"insights":[248],"regarding":[249],"dynamics.":[252]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}