Welcome to DIAPASON

Social-media platforms (e.g. Facebook and Twitter) have become a global phenomenon of communication, where users post messages to convey their opinions, report facts that are happening or show situations of interest. A current line of research consists in crowdsensing, i.e. the analysis and interpretation of the huge amount of information that is daily posted in such platforms.

As a result, we developed DIAPASON, a social-sensing prototype for the smart-city framework that serves to detect problems in the citizen's environment, thus contributing to improving quality of life. In fact, we take an integral approach to the concept of "smart city", where we focus not only on detecting problems related to the quality of the infrastructure and services provided to citizens (e.g. mobility, public works, and community facilities, among others) but also on analysing the sociological dimension of the city, which is reflected through people's concerns (e.g. crime and justice, unemployment, and healthcare, just to name a few). To this end, this project aims to process English and Spanish messages.

Publications, datasets and software

Here are all the publications derived from the project.

Here you can download the DIAPASON ontology.

Here you can download the datasets of English and Spanish tweets that were manually tagged according to a specific social problem: Black Economy, Institutional Elder Abuse, Student Dropout, and Violence Against Women.

Here you can download TexMiLAB (Text-Mining Laboratory), a workbench that allows researchers to do text-mining experiments in two modes: graphical user interface and C# scripting interface.