Modelling the Degree of Emotional Concern: COVID-19 Response in Social Media

The massive impact caused by the COVID-19 pandemic has left no one indifferent, becoming an unprecedented challenge. The use of protections such as sanitary masks has become increasingly common, restrictions in our daily lives, such as social distancing or confinements, have had serious consequences on the economy and our welfare state. Although the measures imposed throughout the world follow the same pattern, they have been applied with different criteria depending on the country. Over extended periods of time, people tend to change their perception of an event and its magnitude, or in other words, they stop being so concerned despite the seriousness of the matter. In this paper, we introduce a new metric to quantify the degree of emotional concern of people being affected by a topic, and we confirm how populations from different countries follow this trend of downplaying the effect of the pandemic and reach a state of indifference. To do this, we propose a method to analyze the social media stream over time extracting the different emotional states from the Russel Circumplex plane and computing the shifting created by the tragic event—the pandemic. We complete this metric by incorporating searching behavior to reflect not only push contents but also pull inquiries. The resulting metric establishes a relationship between the pandemic and the emotional response by defining the degree of Emotional Concern. Although the method can be applied to any location with a significant and varied amount of geo-localized social media streams, the scope of this paper covers the most representative cities in Europe

Integrating Quality Criteria in a Fuzzy Linguistic Recommender System for Digital Libraries

Recommender systems can be used in an academic environment to assist users in their decision making processes to find relevant information. In the literature we can find proposals based in user’ profile or in item’ profile, however they do not take into account the quality of items. In this work we propose the combination of item’ relevance for a user with its quality in order to generate more profitable and accurate recommendations. The system measures item quality and takes it into account as new factor in the recommendation process. We have developed the system adopting a fuzzy linguistic approach.Projects TIN2010-17876, TIC5299 y TIC-599

A risk-aware fuzzy linguistic knowledge-based recommender system for hedge funds

One of the most difficult tasks for hedge funds investors is selecting a proper fund with just the right level level of risk. Often times, the issue is not only quantifying the hedge fund risk, but also the level the investors consider just right. To support this decision, we propose a novel recommender system, which is aware of the risks associated to different hedge funds, considering multiple factors, such as current yields, historic performance, diversification by industry, etc. Our system captures the preferences of the investors (e.g. industries, desired level of risk) applying fuzzy linguistic modeling and provides personalized recommendations for matching hedge funds. To demonstrate how our approach works, we have first profiled more than 4000 top hedge funds based on their composition and performance and second, created different simulated investment profiles and tested our recommendations with them.This paper has been developed with the FEDER financing under Project TIN2016-75850-R

Introducing CSP Dataset: A Dataset Optimized for the Study of the Cold Start Problem in Recommender Systems

Recommender systems are tools that help users in the decision-making process of choosing items that may be relevant for them among a vast amount of other items. One of the main problems of recommender systems is the cold start problem, which occurs when either new items or new users are added to the system and, therefore, there is no previous information about them. This article presents a multi-source dataset optimized for the study and the alleviation of the cold start problem. This dataset contains info about the users, the items (movies), and ratings with some contextual information. The article also presents an example user behavior-driven algorithm using the introduced dataset for creating recommendations under the cold start situation. In order to create these recommendations, a mixed method using collaborative filtering and user-item classification has been proposed. The results show recommendations with high accuracy and prove the dataset to be a very good asset for future research in the field of recommender systems in general and with the cold start problem in particular.Spanish Government PID2019-103880RB-I00Andalusian Agency project P20_0067

Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology

The rapid advances in Web technologies are promoting the development of new pedagogic models based on virtual teaching. In this framework, personalized services are necessary. Recommender systems can be used in an academic environment to assist users in their teaching-learning processes. In this paper, we present a trust based recommender system, adopting a fuzzy linguistic modeling, that provides personalized activities to students in order to reinforce their education, and applied it in the field of oral surgery and implantology. We don’t take into account users with similar ratings history but users in which each user can trust and we provide a method to aggregate the trust information. This system can be used in order to aid professors to provide students with a personalized monitoring of their studies with less effort. The results obtained in the experiments proved to be satisfactory.TIN2016-75850-

Web platform for learning distributed databases’ queries processing

A distributed database is a collection of data stored in different locations of a distributed system. The processing of queries in distributed databases is quite complex but of great importance for information management. Students who have to learn that process have serious difficulties for understanding them. On this work we present a web platform for helping the students learning the processing and optimization of queries in distributed databases. The novelty of this platform is that as far as we know, there is no similar graphical tool. It allows to visualize step by step the different phases of distributed query processing, showing how are they forming, making it easier for the students to understand these concepts. Moreover, having this web platform available, always and everywhere, indirectly have an impact on other competences like encouraging students’ autonomous work and self-learning, adapting the teaching to its one-time necessities and reinforcing the advantages to apply information techniques in the teaching field. The results of the developed tests to validate the platform's functionalities and student's satisfaction were very positive.This work has been developed thanks to the funding of the project PID46-201617 of the Universidad de Jaén

Los recintos universitarios y el alojamiento. Un compromiso de naturaleza urbana

La vida universitaria no se limita a las actividades propias de la docencia y la investigación. Como realidad urbana, participa de un amplio sistema de relaciones y dependencias entre los espacios de alojamiento, de trabajo, de ocio y de movilidad que propician los intercambios de información y las formas de relacionarse más comunes en nuestra cultura. El presente texto plantea algunas cuestiones que relacionan residencia y universidad, entendiéndolas como un binomio inseparable sobre el que avanzar en cuanto a previsiones y a su sistematización futura. Las pautas de localización y las relaciones espaciales entre el alojamiento, los diferentes recintos universitarios y la ciudad se plantean como factores a tener en cuenta, así como los niveles de oferta y demanda en una selección de casos. Una aproximación al tema que intenta aportar algunas claves para la mejora y adecuación del alojamiento universitario en la actualidad.Palabras clave: Alojamiento universitario, villa universitaria, universidad, campus urbano, equipamiento territorial.Abstract: University life is not limited to the activities of teaching and research. As an urban reality, it forms part of a larger system of relationships and dependencies such as the accommodation, work, leisure and mobility spaces which promote the exchange of information and the most common ways of relating with each other in our culture. This paper raises some issues linking residence and university, understanding this pairing as inseparable and over which to move on in terms of forecasts and its future systematization. Localization patterns and spatial relationships between accommodation, different campuses and the city are proposed as factors to be considered, as well as the levels of supply and demand in selected cases. An approach to the topic that tries to provide some clues for the improvement and the adaptation of university accommodation today. Key words: university accommodation, university village, university, urban campus, territorial facility

Solidaridad en la redes sociales: cuando el usuario abandona su zona de confort - el caso de Charlie Hebdo’

The fear of sharing information experiments a decrease as new generations start being active in Social Media platforms. Everybody behaves very homogeneously within their own community, following recurrent communication patterns. But when a tragic event shakes people’s minds, they feel the impulse to break these patterns and communicate their feelings to a bigger audience. In this paper, we analyse this phenomenon, dissecting the communication changes over time, identifying new patterns and discussing our findings in the context of a real scenario, namely the Charlie Hebdo terrorist attack.Las nuevas generaciones se sienten como en casa en las redes sociales. El miedo a compartir información en estas plataformas brilla por su ausencia. El comportamiento de cada uno es muy homogéneo dentro de su propia comunidad, siguiento patrones muy claros y definidos. Cuando un evento trágico sacude los corazones de los usuarios, la necesidad de romper esos patrones para comunicar sus sentimientos a una audiencia mayor se impone. En este trabajo, analizamos este fenómeno, identificando los cambios en la comunicación en el transcurso del tiempo así como nuevos patrones. Para ilustrar nuestro análisis, nos basamos en un caso real, el atentado contra la redacción de Charlie Hebdo en París

Quadratic quantum speedup in evaluating bilinear risk functions

Computing nonlinear functions over multilinear forms is a general problem with applications in risk analysis. For instance in the domain of energy economics, accurate and timely risk management demands for efficient simulation of millions of scenarios, largely benefiting from computational speedups. We develop a novel hybrid quantum-classical algorithm based on polynomial approximation of nonlinear functions and compare different implementation variants. We prove a quadratic quantum speedup, up to polylogarithmic factors, when forms are bilinear and approximating polynomials have second degree, if efficient loading unitaries are available for the input data sets. We also enhance the bidirectional encoding, that allows tuning the balance between circuit depth and width, proposing an improved version that can be exploited for the calculation of inner products. Lastly, we exploit the dynamic circuit capabilities, recently introduced on IBM Quantum devices, to reduce the average depth of the Quantum Hadamard Product circuit. A proof of principle is implemented and validated on IBM Quantum systems

Aproximación Proteómica al síndrome de apneas-hipopneas del sueño

Comunicaciones a congreso