AUTH’s group (OSWINDS : Online Sourced Web INformation Distributed Systems) at the Department of Informatics has strong expertise in the areas of big data analytics, social networks mining and fraud detection as well as on Web mining and content delivery on the Web.The researchers from AUTH will offer advanced research know-how in the areas of sentiment and affective analytics with emphasis on new emerging techniques in the fields of deep learning and fine grained topic detection towards capturing fraud at an early stage.AUTH has established links with the industry due to its involvement and participation at projects, which utilize social networks threads for community, events and phenomena detection. In the ENCASE context, both ERs and ESRs will be seconded to TID in order to develop advanced solutions that involve technologically advanced sentiment and affective analytics in the area of child abuse detection.
Contact information :
Website: https://www.auth.gr/en
Name : Athina Vakali
E-Mail : avakali@csd.auth.gr
Website: https://www.auth.gr/en
Name : Athina Vakali
E-Mail : avakali@csd.auth.gr