During the past decade, tools and techniques for social and geographic data have witnessed substantial changes. For this reason, there is a necessity for investigating methodological and computational aspects in this field. The mapping of tools and techniques for social and geographic data brings two main benefits: it provides an overview of this area, and it also allows researchers to identify potential research agendas for the future.
Explaining the science
New sources of data, such as mobile data and social data, allow researchers to model and understand human behaviour in ways that were not possible just a decade ago. For this reason, in the past few years, there has been an explosion in the development of tools and techniques for the analysis of these 'digital traces' that we leave in our online and offline lives. The goal of this project is to provide an up-to-date overview of the technological landscape in this area in order to underpin future research agendas in this field.
The main purpose of this project is to provide a comprehensive description of the tools and techniques available for the analysis of social and geographic datasets.
During the past decade, there has been an increasing interest in this area from researchers from a variety of disciplines. Traditionally, data were collected through labour-intensive data gathering exercises (census, longitudinal studies, and so on). Instead, nowadays data are retrieved from social networks (user interactions and interests), mobile phones (location data and activity patterns) or IoT sensors (mobility patterns collected by means of card readers at stations, cameras, etc.).
The availability of a large amount of data from these new sources of data allow researchers to investigate different phenomena and processes such as sentiment and opinion analysis, mobility patterns, fake news detection, information spreading, and so on.
The goal of this project is a comprehensive survey that will be of interest for researchers and practitioners in any applied or theoretical area of data science related to the analysis, storage, modelling and visualisation of social and geographic datasets.