Fighting hAte Speech Through a Legal, ICT and Sociolinguistic approach

In a European scenario where online hate speech represents an increasing challenge for national governments, due to its elusiveness and to the lack an efficient reporting and counteracting, FAST LISA will produce a consolidated and cross-border standard protocol designed for local authorities, revolving around the multidisciplinary use of IT tools, legal knowledge and active participation of the youth. METHODOLOGY 1.Design, dedicated to develop the FAST LISA dashboard, a specific tool designed on a state-of-the-art analysis covering legal, linguistic and sociological aspects of hate speech online. The dashboard will use big data from Facebook, Instagram, TikTok and others social networks to draw a sentiment analysis and artificial intelligence engine in order to classify the contents and produce visualization on the community maps. 2.Capacity Building, dedicated to the delivery of the project’s training programme addressing groups of young adults in the 3 FAST LISA target cities/areas: Ravenna in Italy, Santa Coloma in Spain and Offenbach region in Germany. 3.Engage, leading youngsters, experts, cities and local authorities, to become engaged FAST LISA agents by developing pilot actions at local level, both on a community and on an institutional level. IMPACT 1.Involvement of youth through a capacity building programme, international peer learning activities and pilot actions to be developed in cooperation with project partners, making them agents of the project at local level. 2.Creation of the FAST LISA dashboard, engaging authorities through working groups to develop an inventory of legislative instruments as examples of successful initiatives to be replicated. 3.Involve authorities through a policy co-design process generating City Strategies specifically focused on fighting hate speech online in their communities by using the FAST LISA dashboard. 4.Offer NGOs/CSOs an access to advanced data gathering, analysis of trends and triggers of online hatred.