Please use this identifier to cite or link to this item:
Title: Visualizing and ranking the influence of users who post memes in social networks
Author: Pérez Onielfa, Carles
Director/Tutor: Escalera Guerrero, Sergio
Casacuberta, Carles
Keywords: Teoria de grafs
Anàlisi multivariable
Treballs de fi de grau
Xarxes neuronals convolucionals
Aprenentatge automàtic
Xarxes socials en línia
Graph theory
Multivariate analysis
Computer software
Convolutional neural networks
Machine learning
Bachelor's theses
Online social networks
Issue Date: 13-Jun-2022
Abstract: [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.
Note: Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Sergio Escalera Guerrero i Carles Casacuberta
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica
Programari - Treballs de l'alumnat
Treballs Finals de Grau (TFG) - Matemàtiques

Files in This Item:
File Description SizeFormat 
tfg_perez_onielfa_carles.pdfMemòria11.51 MBAdobe PDFView/Open
codi_font_perez_onielfa_carles.zipCodi font74.3 kBzipView/Open

This item is licensed under a Creative Commons License Creative Commons