Deciding which film is the best or which portfolio is the best for investment are examples of decisions made by people every day. Decision-making systems aim to help people make such choices. In general, a decision-making system processes and analyses the available information to arrive at the best alternative solution of the problem of interest. In the preference modelling framework, decision-making systems select the best alternative(s) by maximising a score or choice function defined by the decision makers’ expressed preferences on the set of feasible alternatives. Nevertheless, decision-making systems may have logical errors that cannot be appreciated by developers. The main contribution of this paper is the provision of a verification theorem of the score function based on the quantifier-guided dominance degree (QGDD) with the mean operator in the context of additive preference relations. The provided theorem has several benefits because it can be applied to verify that the result obtained is correct and that there are no problems in the programming of the corresponding decision-making systems, thus improving their reliability. Moreover, this theorem acts on different parts of such systems, since not only does the theorem verify that the order of alternatives is correct, but it also verifies that the creation of the global preference relation is correct.

Social networks are the preferred mean for experts to share their knowledge and provide information. Therefore, it is one of the best sources that can be used for obtaining data that can be used for a high amount of purposes. For instance, determining social needs, identifying problems, getting opinions about certain topics, ... Nevertheless, this kind of information is difficult for a computational system to interpret due to the fact that the text is presented in free form and that the information that represents is imprecise. In this paper, a novel method for extracting information from social networks and represent it in a fuzzy ontology is presented. Sentiment analysis procedures are used in order to extract information from free text. Moreover, multi-granular fuzzy linguistic modelling methods are used for converting the information into the most suitable representation mean.

This paper describes an empirical study carried out with 40 Spanish deaf people, users of sign language, between 19 and 45 years of age, which gathers their perceptions of aspects related to the incidence of the COVID-19 pandemic and its repercussions. During the pandemic, people with hearing disabilities, among other groups, were forgotten. They suffered from accessibility problems to the information issued by the authorities, violating their right to be informed and exposing their health to COVID-19. In this work, we identify the problems they suffered and what effects COVID-19 had on their lives. This will help to take the appropriate measures to restore their rights and design policies and strategies to deal with any new future health emergency. For this, an ad hoc questionnaire was designed, adapted to easy reading and sign language. This was publicized via email and WhatsApp through the Association of Deaf People of Granada and Province (Spain) and was responded to online and by video call with the collaboration of sign language interpreters using the LimeSurvey platform. The results discover (1) the difficulties of communication barriers in the relationship with health professionals and institutions, as well as in the spheres of work and education, (2) similarities with the rest of the population in the negative effects of confinement, and (3) presence of positive effects, such as the development of positive activities and emotions. The study highlights the need to increase economic and institutional support aimed at improving coping resources, access to information, and the reduction of social and institutional barriers that would allow people with hearing disabilities to successfully face future health problems of a global nature such as that experienced with COVID-19.