The aim of the study is to analyse the opportunities and challenges of emergency remote teaching based on experiences of the COVID-19 emergency. A qualitative research method was undertaken in two steps. In the first step, a thematic analysis of an online discussion forum with international experts from different sectors and countries was carried out. In the second step (an Italian case study), both the data and the statements of opinion leaders from secondary online sources, including web articles, statistical data and legislation, were analysed. The results reveal several technological, pedagogical and social challenges. The technological challenges are mainly related to the unreliability of Internet connections and many students’ lack of necessary electronic devices. The pedagogical challenges are principally associated with teachers’ and learners’ lack of digital skills, the lack of structured content versus the abundance of online resources, learners’ lack of interactivity and motivation and teachers’ lack of social and cognitive presence (the ability to construct meaning through sustained communication within a community of inquiry). The social challenges are mainly related to the lack of human interaction between teachers and students as well as among the latter, the lack of physical spaces at home to receive lessons and the lack of support of parents who are frequently working remotely in the same spaces. Based on the lessons learned from this worldwide emergency, challenges and proposals for action to face these same challenges, which should be and sometimes have been implemented, are provided.

Fake news detection has gained increasing importance among the research community due to the widespread diffusion of fake news through media platforms. Many dataset have been released in the last few years, aiming to assess the performance of fake news detection methods. In this survey, we systematically review twenty-seven popular datasets for fake news detection by providing insights into the characteristics of each dataset and comparative analysis among them. A fake news detection datasets characterization composed of eleven characteristics extracted from the surveyed datasets is provided, along with a set of requirements for comparing and building new datasets. Due to the ongoing interest in this research topic, the results of the analysis are valuable to many researchers to guide the selection or definition of suitable datasets for evaluating their fake news detection methods.

Italy's recent history is punctuated with devastating flood disasters claiming high death toll and causing vast but underestimated economic, social and environmental damage. The responses to major flood and landslide disasters such as the Polesine (1951), Vajont (1963), Firenze (1966), Valtelina (1987), Piedmont (1994), Crotone (1996), Sarno (1998), Soverato (2000), and Piedmont (2000) events have contributed to shaping the country's flood risk governance. Insufficient resources and capacity, slow implementation of the (at that time) novel risk prevention and protection framework, embodied in the law 183/89 of 18 May 1989, increased the reliance on the response and recovery operations of the civil protection. As a result, the importance of the Civil Protection Mechanism and the relative body of norms and regulation developed rapidly in the 1990s. In the aftermath of the Sarno (1998) and Soverato (2000) disasters, the Department for Civil Protection (DCP) installed a network of advanced early warning and alerting centres, the cornerstones of Italy's preparedness for natural hazards and a best practice worth following. However, deep convective clouds, not uncommon in Italy, producing intense rainfall and rapidly developing localised floods still lead to considerable damage and loss of life that can only be reduced by stepping up the risk prevention efforts. The implementation of the EU Floods Directive (2007/60/EC) provides an opportunity to revise the model of flood risk governance and confront the shortcomings encountered during more than 20 yr of organised flood risk management. This brief communication offers joint recommendations towards this end from three projects funded by the 2nd CRUE ERA-NET (http://www.crue-eranet.net/) Funding Initiative: FREEMAN, IMRA and URFlood.

Emotion classification is a research area in which there has been very intensive literature production concerning natural language processing, multimedia data, semantic knowledge discovery, social network mining, and text and multimedia data mining. This paper addresses the issue of emotion classification and proposes a method for classifying the emotions expressed in multimodal data extracted from videos. The proposed method models multimodal data as a sequence of features extracted from facial expressions, speech, gestures, and text, using a linguistic approach. Each sequence of multimodal data is correctly associated with the emotion by a method that models each emotion using a hidden Markov model. The trained model is evaluated on samples of multimodal sentences associated with seven basic emotions. The experimental results demonstrate a good classification rate for emotions.

Current management of disaster risks is often fragmented due to a lack of coordination between involved actors, i.e. civil protection and spatial planning – a phenomenon which is known as the "problem of interplay". This paper presents an output-oriented risk management approach ("parametric governance"). Here, the modality of the achievement of objectives remains in the hands of the given addressees. This implies a shift from a top-down to a more collaborative, process-oriented form of decision-making. The approach has been successfully applied in two hazard cases and three administrative contexts: (a) the City of Dortmund (Germany) facing flash floods, (b) East Attica region (Greece) facing forest fires, and (c) Lazio Region (Italy) also facing forest fires. As proved by the applications of the concept, a dialogue among experts, stakeholders, and decision-makers is indispensable in order to guarantee inclusion of all diverse and competing values, opinions, and claims. Moreover, a structured communication path is needed to meet the requirements of a risk governance process. Finally, a win-win-situation among the involved actors has to be created to reach an agreement on common goals and actions to achieve them in due time.