Twitter engagement model for RecSys Challenge 2021

dc.contributor.advisorSeguí Mesquida, Santi
dc.contributor.advisorGilabert Roca, Pere
dc.contributor.authorMoreno Blanco, Marcos
dc.contributor.authorTorralba Agell, Adrià
dc.date.accessioned2022-05-24T07:13:00Z
dc.date.available2022-05-24T07:13:00Z
dc.date.issued2021-07-01
dc.descriptionTreballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona. Curs: 2020-2021. Tutor: Santi Seguí Mesquida i Pere Gilabert Rocaca
dc.description.abstract[en] Recommendation systems is an interesting and wide field of research and it is present in a huge amount of different areas in our daily life. The RecSys ACM conference is the most important conference in the recommendation area and every year they organise a competition: the RecSys Challenge. The work presented here aims to solve the RecSys 2021 Challenge which consists of giving a probability to two Twitter users that interact. In this project we have worked in the development of a model which uses the power of Gradient Boosting Trees to combine multiple hand-crafted features in an aim to represent the interaction between the users. Our team reached the 14th place in the overall challenge leaderboard and is placed between the 7th and the 9th place in terms of Like overall performance.ca
dc.format.extent60 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/185952
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Marcos Moreno Blanco i Adrià Torralba Agell, 2021
dc.rightscodi: GPL (c) Marcos Moreno Blanco i Adrià Torralba Agell, 2021
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.rights.urihttp://www.gnu.org/licenses/gpl-3.0.ca.html*
dc.sourceMàster Oficial - Fonaments de la Ciència de Dades
dc.subject.classificationSistemes d'ajuda a la decisió
dc.subject.classificationXarxes socials en línia
dc.subject.classificationTeoria de la predicció
dc.subject.classificationTreballs de fi de màster
dc.subject.classificationDades massivesca
dc.subject.otherDecision support systems
dc.subject.otherOnline social networks
dc.subject.otherPrediction theory
dc.subject.otherMaster's theses
dc.subject.otherBig dataen
dc.titleTwitter engagement model for RecSys Challenge 2021ca
dc.typeinfo:eu-repo/semantics/bachelorThesisca

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