{"id":"https://openalex.org/W2740709407","doi":"https://doi.org/10.24963/ijcai.2017/373","title":"LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity","display_name":"LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2740709407","doi":"https://doi.org/10.24963/ijcai.2017/373","mag":"2740709407"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/373","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/373","pdf_url":"https://www.ijcai.org/proceedings/2017/0373.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0373.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058145190","display_name":"Bidisha Samanta","orcid":"https://orcid.org/0000-0002-0000-2650"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bidisha Samanta","raw_affiliation_strings":["IIT Kharagpur","Indian Institute of Technology Kharagpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur","institution_ids":["https://openalex.org/I145894827"]},{"raw_affiliation_string":"Indian Institute of Technology Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026269420","display_name":"Abir De","orcid":"https://orcid.org/0000-0002-9062-3636"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abir De","raw_affiliation_strings":["IIT Kharagpur","Indian Institute of Technology Kharagpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur","institution_ids":["https://openalex.org/I145894827"]},{"raw_affiliation_string":"Indian Institute of Technology Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040381142","display_name":"Abhijnan Chakraborty","orcid":"https://orcid.org/0000-0003-0908-1639"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Abhijnan Chakraborty","raw_affiliation_strings":["IIT Kharagpur","Indian Institute of Technology Kharagpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur","institution_ids":["https://openalex.org/I145894827"]},{"raw_affiliation_string":"Indian Institute of Technology Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073812421","display_name":"Niloy Ganguly","orcid":"https://orcid.org/0000-0002-3967-186X"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Niloy Ganguly","raw_affiliation_strings":["IIT Kharagpur","Indian Institute of Technology Kharagpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Kharagpur","institution_ids":["https://openalex.org/I145894827"]},{"raw_affiliation_string":"Indian Institute of Technology Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058145190"],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":3.4529,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.94367992,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2679","last_page":"2685"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9987000226974487,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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/popularity","display_name":"Popularity","score":0.9832030534744263},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8440343737602234},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7513582110404968},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6684350967407227},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6190269589424133},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6105314493179321},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.5125339031219482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4063539206981659},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3632497489452362},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.35889488458633423},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35410672426223755}],"concepts":[{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.9832030534744263},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8440343737602234},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7513582110404968},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6684350967407227},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6190269589424133},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6105314493179321},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.5125339031219482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4063539206981659},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3632497489452362},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35889488458633423},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35410672426223755},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2017/373","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/373","pdf_url":"https://www.ijcai.org/proceedings/2017/0373.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/373","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/373","pdf_url":"https://www.ijcai.org/proceedings/2017/0373.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740709407.pdf","grobid_xml":"https://content.openalex.org/works/W2740709407.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1954020979","https://openalex.org/W2006915310","https://openalex.org/W2018005216","https://openalex.org/W2018165284","https://openalex.org/W2040811557","https://openalex.org/W2080290417","https://openalex.org/W2095016473","https://openalex.org/W2096845327","https://openalex.org/W2097180027","https://openalex.org/W2112056172","https://openalex.org/W2141250202","https://openalex.org/W2149260218","https://openalex.org/W2164227199","https://openalex.org/W2164900957","https://openalex.org/W2235388212","https://openalex.org/W2268112941","https://openalex.org/W2295521688","https://openalex.org/W2330168953","https://openalex.org/W2337540978","https://openalex.org/W2340452757","https://openalex.org/W2467174000","https://openalex.org/W2489369235","https://openalex.org/W2737428849","https://openalex.org/W2760852995","https://openalex.org/W2768149277","https://openalex.org/W2949377321","https://openalex.org/W2951851909","https://openalex.org/W2952861497","https://openalex.org/W2953100823","https://openalex.org/W2963195304","https://openalex.org/W2963597852","https://openalex.org/W2964232927","https://openalex.org/W2964269387","https://openalex.org/W3122471732","https://openalex.org/W4255759781"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2477036161","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W4294565801","https://openalex.org/W2170801710","https://openalex.org/W2952704802","https://openalex.org/W2741781807"],"abstract_inverted_index":{"Predicting":[0],"the":[1,20,27,30,64,77,83,89,118,128],"popularity":[2,21,28,86,105],"dynamics":[3],"of":[4,11,22,29,85,88,121],"Twitter":[5],"hashtags":[6,91],"has":[7],"a":[8,54,109],"broad":[9],"spectrum":[10],"applications.":[12],"Existing":[13],"works":[14],"have":[15],"mainly":[16],"focused":[17],"on":[18,96],"modeling":[19],"individual":[23],"tweets":[24],"rather":[25],"than":[26],"underlying":[31],"hashtags.":[32],"Hence,":[33],"they":[34],"do":[35],"not":[36],"consider":[37],"several":[38],"realistic":[39],"factors":[40,66],"for":[41],"hashtag":[42,72,78],"popularity.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47],"propose":[48],"Large":[49],"Margin":[50],"Point":[51],"Process":[52],"(LMPP),":[53],"probabilistic":[55],"framework":[56],"that":[57,101],"integrates":[58],"hashtag-tweet":[59],"influence":[60],"and":[61],"hashtag-hashtag":[62],"competitions,":[63,79],"two":[65],"which":[67],"play":[68],"important":[69],"roles":[70],"in":[71],"propagation.":[73],"Furthermore,":[74],"while":[75],"considering":[76],"LMPP":[80,102,114],"looks":[81],"into":[82],"variations":[84],"rankings":[87,120],"competing":[90,122],"across":[92],"time.":[93],"Extensive":[94],"experiments":[95],"seven":[97],"real":[98],"datasets":[99],"demonstrate":[100],"outperforms":[103],"existing":[104],"prediction":[106],"approaches":[107],"by":[108],"significant":[110],"margin.":[111],"Going":[112],"further,":[113],"can":[115],"accurately":[116],"predict":[117],"relative":[119],"hashtags,":[123],"offering":[124],"additional":[125],"advantage":[126],"over":[127],"state-of-the-art":[129],"baselines.":[130]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
