Escalera Guerrero, SergioCasacuberta, CarlesPérez Onielfa, Carles2023-01-132023-01-132022-06-13https://hdl.handle.net/2445/192142Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Sergio Escalera Guerrero i Carles Casacuberta[en] Memes evolve and mutate through their diffusion in social media. They have the potential to propagate ideas and, by extension, products. Many studies have focused on memes, but none so far, to our knowledge, on the users who post them, their relationships, and the reach of their influence. In this project, we define a meme influence graph together with suitable metrics to visualize and quantify influence between users who post memes. Then, we describe a process to implement our definitions using a new approach to meme detection based on text- to-image area ratio and contrast. After applying our method to a set of users of the Instagram platform, we conclude that our metrics add information to already existing user characteristics and that our methodology can also be used to study the popularity of memes types among the users.48 p.application/pdfengmemòria: cc-nc-nd (c) Carles Pérez Onielfa, 2022codi: GPL (c) Carles Pérez Onielfa, 2022http://creativecommons.org/licenses/by-nc-nd/3.0/es/http://www.gnu.org/licenses/gpl-3.0.ca.htmlTeoria de grafsAnàlisi multivariableProgramariTreballs de fi de grauXarxes neuronals convolucionalsAprenentatge automàticXarxes socials en líniaMemsGraph theoryMultivariate analysisComputer softwareConvolutional neural networksMachine learningBachelor's thesesOnline social networksinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess