Eines basades en text per a la visualització i geolocalització de notícies

Abstract

This project came up after a few meetings with the professor Dr. Jordi Vitrià talking about Data Science, the possibilities inside this sector, about interesting projects that people made using Data Science, we talked about some cases that could be interesting to analyse, all with a spot in mind, the possibility of reaching a result and visualize that result in an understandable way. So, after those inspiring meetings we achieved the main idea of this project: Geolocation of news. Regarding the journalism sector, hundreds of news are published every day, but unfortunately not all of them include a proper geographic reference. All those news with a reference to a geographic location let the door open to a new way of distribution, and also let new ways of analysis based on this new parameter, the location. As an example, imagine that a developer wants to let a user with a smartphone or a tablet, receive automatically the news related to the place where the user is. Without a reference to where the news took place it is difficult to face the problem, however with a reference to a place the problem now seems affordable. During the realization of this project, various tools and methods are used in order to obtain automatically a set of georeferenced tags from the news and thus be able to show the results in an easy way to analyse. Despite being this project based in the concept of Data Science, I am not explicitly using algorithms from the world of Data Science (in this report I will explain the reasons why some algorithms could not be used), I follow, however, the main principles: look for databases that can help me face the problem, clean all data in order to be able to use it, and finally I try to show the results in an understandable way to reach results or conclusions. This document outlined in detail the design, development and implementation of every single step that was necessary to achieve the final result. In order to see the results in a simple way, I also created a website with a summary of all the project and some visualizations of the results under the following URL: http://alsolanes.github.io/TFG