Publication: Análisis de bulos en Twitter
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2022
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Abstract
Al igual que las nuevas tecnologías han evolucionado rápidamente, los medios de comunicación se han visto obligados a progresar de forma paralela para no quedarse rezagados. Es por ello que la aparición de Internet y los dispositivos móviles han facilitado que los medios de información puedan llegar a todo el mundo de una manera más rápida y sencilla gracias a ello.
Internet ha tenido un gran papel en los últimos años en el ámbito periodístico. Ya que la información se difunde a gran escala y velocidad y el ciudadano tiene gran cantidad de información a su disposición, pero, podríamos decir, que no ha sido formado para saber cómo interpretarla o utilizarla. Es aquí donde entran los bulos.
Un bulo es una noticia falsa, a menudo de carácter sensacionalista, creada para ser ampliamente compartida o distribuida con el fin de generar ingresos, o promover o desacreditar a una figura pública, movimiento político, empresa, etc.
Estos bulos afectan gravemente al correcto funcionamiento de un sistema democrático y se está intentando erradicar desde los estados y las organizaciones supranacionales.
Es por esto, que este proyecto se ha enfocado en estudiar la viabilidad de los diferentes algoritmos de clasificación, para detectar bulos a través de machine learning, teniendo en cuenta las implicaciones sociales y políticas del consumo masivo de este tipo de noticias que circulan a través de Twitter, la red social la cual se ha vuelto cada vez más popular, incluso llegandose a convertir en el sitio de microblogging más utilizado con más de 330 millones de usuarios y generando unos 500 millones de mensajes al día, siendo así en una fuente de información muy grande.
Just as new technologies have evolved rapidly, the media have been forced to make parallel progress so as not to lag behind. That is why the emergence of the Internet and mobile devices has made it easier for the media to reach everyone faster and easier. The Internet has played a great role in recent years in the field of journalism. Because information is disseminated on a large scale and at speed and the citizen has a great deal of information at his disposal, but, we could say, he has not been trained to know how to interpret or use it. This is where the hoaxes come in. A hoax is false news, often sensationalist in nature, created to be widely shared or distributed in order to generate income, or to promote or discredit a public figure, political movement, enterprise, etc. These hoaxes seriously affect the proper functioning of a democratic system and attempts are being made to eradicate them from supranational states and organizations. This is why this project has focused on studying the feasibility of different classification algorithms, to detect fake news through machine learning, taking into account the social and political implications of the massive consumption of this type of news circulating through Twitter, the social network which has become increasingly popular, even becoming the most used microblogging site with more than 330 million users and generating about 500 million messages a day, thus being a very large source of information.
Just as new technologies have evolved rapidly, the media have been forced to make parallel progress so as not to lag behind. That is why the emergence of the Internet and mobile devices has made it easier for the media to reach everyone faster and easier. The Internet has played a great role in recent years in the field of journalism. Because information is disseminated on a large scale and at speed and the citizen has a great deal of information at his disposal, but, we could say, he has not been trained to know how to interpret or use it. This is where the hoaxes come in. A hoax is false news, often sensationalist in nature, created to be widely shared or distributed in order to generate income, or to promote or discredit a public figure, political movement, enterprise, etc. These hoaxes seriously affect the proper functioning of a democratic system and attempts are being made to eradicate them from supranational states and organizations. This is why this project has focused on studying the feasibility of different classification algorithms, to detect fake news through machine learning, taking into account the social and political implications of the massive consumption of this type of news circulating through Twitter, the social network which has become increasingly popular, even becoming the most used microblogging site with more than 330 million users and generating about 500 million messages a day, thus being a very large source of information.
Description
Trabajo de Fin de Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de Arquitectura de Computadores y Automática, Curso 2021/2022.