This module is the most extensive proposed by the project, as it incorporates the tasks with the greatest research burden. Following the detailed analysis of the domains, scenarios, current techniques, information sources, as well as the specific challenges to be solved, in this module we will identify the expected response of future solutions. The module will explore new methods and techniques that break the state of the art and provide a breakthrough in the search for solutions to the problems indicated. To model digital content, all the information related to the context where this content is produced and consumed is relevant: its textual content, the profiles of the digital entities involved in the exchange, the network structure maintained by these entities. This requires a novel approach to the construction of models, which must deal with heterogeneous features (text, network structure, temporal evolution, additional features present…). From feature engineering to end-to-end solutions, the holistic reality of digital content must be considered in the search for models that allow inference processes (classification and decision making) in the detection of both beneficial (hope-speech and secure content) and malicious (hate-speech and fake news) content.