An´Alisis Y Modelizaci´On De La Din´Amica Emergente Durante El Proceso De Difusi´On De Informaci´On En Las Redes Sociales D

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An´Alisis Y Modelizaci´On De La Din´Amica Emergente Durante El Proceso De Difusi´On De Informaci´On En Las Redes Sociales D UNIVERSIDAD POLITECNICA´ DE MADRID ESCUELA TECNICA´ SUPERIOR DE INGENIEROS AGRONOMOS´ ANALISIS´ Y MODELIZACION´ DE LA DINAMICA´ EMERGENTE DURANTE EL PROCESO DE DIFUSION´ DE INFORMACION´ EN LAS REDES SOCIALES DE INTERNET ALFREDO JOSE´ MORALES GUZMAN´ Ingeniero en Telecomunicaci´on M´asteren F´ısica de Sistemas Complejos TESIS DOCTORAL 2014 ii GRUPO DE SISTEMAS COMPLEJOS ESCUELA TECNICA´ SUPERIOR DE INGENIEROS AGRONOMOS´ ANALYZING AND MODELING THE EMERGENT DYNAMICS DURING THE INFORMATION DIFFUSION PROCESS ON INTERNET SOCIAL NETWORKS ALFREDO JOSE´ MORALES GUZMAN´ Telecommunications Engineer MSc in Physics of Complex Systems Advisor: ROSA MAR´IA BENITO ZAFRILLA PhD in Chemistry Sciences 2014 ii A mi madre Kalena, por ser mi ejemplo ii AGRADECIMIENTOS En primer lugar, quiero agradecer a la Dra. Rosa Mar´ıaBenito Zafrilla por su incansable labor como directora de esta tesis. Durante estos a~nos,con mucha paciencia y tes´on,me ha ense~nadocon gran firmeza la labor de la investigaci´oncient´ıficay los est´andaresde la excelencia. Especialmente, le estar´einfinitamente agradecido por haberme dado esa primera oportunidad, que sin ser conciente, cambi´oel rumbo de mi vida para siempre. Por otra parte, quiero agradecerle a mis profesores, colaboradores y compa~nerosdel Grupo de Sistemas Complejos de la Universidad Polit´ecnicade Madrid. Sin sus ense~nanzas, aportes, consejos y apoyo, el trabajo realizado durante estos a~nosno hubiera sido el mismo. Con especial cari~nome gustar´ıarecordar a los profesores: Juan Carlos Losada, Werner Creix- ell (visitante), Javier Galeano, Ram´onAlonso, Miguel A. Porras y Ana Tarquis. As´ıcomo a mis compa~nerosdel laboratorio: Javier Borondo, Fabio Revuelta, Izaskun Oregui, Pedro Ben´ıtez, Henar Hernandez, Johan Mart´ınezy Maxi Fern´andez. Adem´as,debo agradecer a la Universidad Polit´ecnicade Madrid por otorgarme la beca UPM-BSCH, sin la cual, la culminaci´onde este trabajo hubiera sido imposible. As´ımismo me gustar´ıaagradecer a los miembros del New England Complex Systems Institute, donde tuve el gusto de realizar una estancia de movilidad. En especial, me gustar´ıa agradecer al prof. Yaneer Bar-Yam por haberme dado la oportunidad de colaborar con el instituto, as´ıcomo al prof. Hiroki Sayama por sus aportes en la labor investigativa. Por otra parte, me gustar´ıarecordar a mis compa~nerosde trabajo: Debra Gorfine, Francisco Prieto, Joe Norman, Maya Bialik, Vaibhav Vavilala, Molly Wexler-Romig, Vincent Wong, Lili y Katriel Friedman. Tambi´enquiero agradecer a mis colaboradores de Global Pulse de las Naciones Unidas, Telef´onicaDigital y Centro de Innovaci´onen Tecnolog´ıa para el Desarrollo Humano de la Universidad Polit´ecnicade Madrid, por haberme dado la oportunidad de trabajar y apren- der de ellos en un proyecto conjunto. En especial, quiero agradecer y recordar a Miguel A. Luengo-Oroz, David Pastor, Yolanda Torres, Vanessa Fr´ıas-Mart´ınez y Enrique Fr´ıas- Mart´ınez. iii Adem´as,quiero agradecer a todas las personas, amigos y familiares que me acompa~naron durante este largo viaje. En primer lugar, quiero recordar a mi padre, suegros, hermanos, cu~nados,abuela, t´ıas,sobrinos y primos, que con su cari~noincondicional me dieron las fuerzas necesarias para emprender este camino. Por otra parte, quiero agradecer a mis amigos de vida Zhandra, Edu, Patricia, Sergio, Laura, Andrei, Iuri, Cesar y Carolina, que con su apoyo y compa~n´ıame hicieron el viaje mas placentero. Finalmente, quiero agradecer de forma absoluta a mi esposa, Vanessa Pechiaia, coautora honor´ıficade esta tesis. Su apoyo y amor inagotable fueron la base fundamental para la realizaci´onde este trabajo. A ella, mi mas profunda gratitud por haber hecho de ´esta,otra de las mejores etapas de mi vida. Por ´ultimo,he de decir con mucho honor, que este trabajo est´adedicado a mi madre, el pilar fundamental de mi vida. Fue ella la primera persona en animarme a tomar este camino y en darme su absoluta confianza para recorrerlo con ´exito. Sin palabras capaces de expresarle mi profunda admiraci´on,le agradecer´eeternamente por ser mi ejemplo a seguir y constante motivo de inspiraci´on. Desde el fondo de mi coraz´on,gracias a todos. iv RESUMEN Durante la actividad diaria, la sociedad actual interact´uaconstantemente por medio de dispositivos electr´onicosy servicios de telecomunicaciones, tales como el tel´efono,correo electr´onico,transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosi´onsin precedentes de estudios de sistemas sociales, dirigidos por el an´alisis de datos y procesos computacionales. En esta tesis desarrollamos m´etodos computacionales y matem´aticospara analizar sis- temas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teor´ıade redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emer- gentes de interacciones sociales en los nuevos espacios tecnol´ogicos,tales como la red social Twitter y la telefon´ıam´ovil.Analizamos los sistemas por medio de la construcci´onde redes complejas y series temporales, estudiando su estructura, funcionamiento y evoluci´on en el tiempo. Tambi´en,investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, as´ıcomo medimos el impacto de eventos cr´ıticosen el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la din´amicaemergente con que fluye la informaci´onen el sistema. Para los estudios de la red social Twitter, hemos basado nuestros an´alisisen conversa- ciones puntuales, tales como protestas pol´ıticas, grandes acontecimientos o procesos elec- torales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Espec´ıficamente, constru- imos una red para representar qui´enrecibe los mensajes de qui´en y otra red para representar qui´enpropaga los mensajes de qui´en. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topolog´ıade estas redes, hemos indentificado tres tipos de v usuarios que determinan el flujo de informaci´onseg´unsu actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el n´umerode retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuer- zos individuales sobre la reacci´oncolectiva. Hemos observado que la distribuci´onde esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relaci´onentre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribuci´onde eficiencia, hemos desarrollado un modelo computacional que simula la propagaci´onde mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribuci´onde eficiencia, tanto la topolog´ıade la red social subyacente, como la forma en que los usuarios env´ıanmensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado t´ecnicaspara inferir el grado de polarizaci´onpol´ıtica en redes sociales. Proponemos una metodolog´ıapara estimar opiniones en redes sociales y medir el grado de polarizaci´onen las opiniones obtenidas. Hemos dise~nadoun modelo donde estudiamos el efecto que tiene la opini´onde un peque~nogrupo de usuarios influyentes, lla- mado ´elite, sobre las opiniones de la mayor´ıade usuarios. El modelo da como resultado una distribuci´onde opiniones sobre la cual medimos el grado de polarizaci´on. Aplicamos nues- tra metodolog´ıapara medir la polarizaci´onen redes de difusi´onde mensajes, durante una conversaci´onen Twitter de una sociedad pol´ıticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodolog´ıapropuesta es capaz de determinar diferentes grados de polarizaci´onde- pendiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefon´ıa m´ovil.Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comu- nicaci´onse alteran de forma abrupta en las ´areasafectadas por la cat´astofre.Con lo cual, demostramos que se podr´ıamedir el impacto en la regi´oncasi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de ac- tividad y movilidad humana para caracterizar las interacciones entre regiones de un pa´ısen desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. vi En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del
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