Abstract
Social networks are strongly present in the daily life of modern society. Most people use these social networks to share information about their lives, their opinions, places they visit and their state of mind. Generally, these posts are composed of various information, being the location of the users location part of the data. The purpose of this work is to obtain the location of the posts and observe the users mobility pattern in the city of Porto, Portugal. This paper discusses the technologies available for obtaining the data, the social networks currently worth studying and their respective restrictions. It also explores new approaches to collect the data from the desired social networks, respecting all restrictions currently applied. The different software solutions developed for the social networks interactions are explored and described in depth. Subsequently, the necessary software for social networks is reviewed, the possible algorithms for data mining are discussed and its implementation is presented. Finally, the results obtained are interpreted and studied according to the characteristics of the city, tourism promotions and transport routes.
1. Main Text
As the population grows exponentially around the world, most urban planning methodologies have also had to evolve to integrate the latest technologies and ensure that processes do not become obsolete. Urban planning is the subject responsible for designing, building and developing the land, air and water resources to better serve the population. It is also responsible for subjects like infrastructure, communications, distribution and public transportation. McGill The study of people’s mobility provides information on public transport infrastructure and routes, police distribution and road development. Not so long ago, these studies were expensive and long. However, nowadays people are willing to share personal information through smartphone apps.
5. Conclusions And Future Work
First of all, this research proved to be possible to still use location based social networks for collecting data while being subject to many restrictions due to GDPR. Then, the data collected provided enough information and details for drawing meaningful conclusions about users mobility patterns.
