Information Management in Healthcare and Environment: Towards an Automatic System for Fake News Detection

[EN] Comments and information appearing on the internet and on different social media sway opinion concerning potential remedies for diagnosing and curing diseases. In many cases, this has an impact on citizens' health and affects medical professionals, who find themselves having to defend their diagnoses as well as the treatments they propose against ill-informed patients. The propagation of these opinions follows the same pattern as the dissemination of fake news about other important topics, such as the environment, via social media networks, which we use as a testing ground for checking our procedure. In this article, we present an algorithm to analyse the behaviour of users of Twitter, the most important social network with respect to this issue, as well as a dynamic knowledge graph construction method based on information gathered from Twitter and other open data sources such as web pages. To show our methodology, we present a concrete example of how the associated graph structure of the tweets related to World Environment Day 2019 is used to develop a heuristic analysis of the validity of the information. The proposed analytical scheme is based on the interaction between the computer tool-a database implemented with Neo4j-and the analyst, who must ask the right questions to the tool, allowing to follow the line of any doubtful data. We also show how this method can be used. We also present some methodological guidelines on how our system could allow, in the future, an automation of the procedures for the construction of an autonomous algorithm for the detection of false news on the internet related to health.The first-named and the forth-named authors were supported by the Spanish Ministry for Science, Innovation and Universities, the Spanish State Research Agency and the European Regional Development Fund under Research Grant SO2015-65594-C2-1R Y 2R, and to the Catedra de Transparencia y Gestion de Datos UPV/GVA. The third-named author was supported by the Spanish Ministry for Science, Innovation and Universities, the Spanish State Research Agency and the European Regional Development Fund under Research Grant MTM2016-77054-C2-1-P.Lara-Navarra, P.; Falciani, H.; Sánchez Pérez, EA.; Ferrer Sapena, A. (2020). Information Management in Healthcare and Environment: Towards an Automatic System for Fake News Detection. International Journal of Environmental research and Public Health (Online). 17(3):1-12. https://doi.org/10.3390/ijerph17031066S112173Sato, A. P. S. (2018). What is the importance of vaccine hesitancy in the drop of vaccination coverage in Brazil? Revista de Saúde Pública, 52, 96. doi:10.11606/s1518-8787.2018052001199Los ministerios de Sanidad y Ciencia realizan un primer listado de 73 pseudoterapiashttp://www.rtve.es/noticias/20190228/ministerios-sanidad-ciencia-realizan-primer-listado-73-pseudoterapias/1892081.shtmlPsoriasis, lupus, alergia… Enfermedades autoinmunes crónicas, o no?https://tunaturopata.es/psoriasis-lupus-autoinmune-tratamiento-natural/Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., … Zittrain, J. L. (2018). The science of fake news. Science, 359(6380), 1094-1096. doi:10.1126/science.aao2998Zannettou, S., Sirivianos, M., Blackburn, J., & Kourtellis, N. (2019). The Web of False Information. Journal of Data and Information Quality, 11(3), 1-37. doi:10.1145/3309699McClain, C. R. (2017). Practices and promises of Facebook for science outreach: Becoming a «Nerd of Trust». PLOS Biology, 15(6), e2002020. doi:10.1371/journal.pbio.2002020Social-H2-2018-report Global Web Index Reporthttps://www.globalwebindex.com/reports/socialWhite Paper: Redefining Financial Risk and Compliance Practiceshttps://neo4j.com/whitepapers/financial-risk-reporting/Akoglu, L., Tong, H., & Koutra, D. (2014). Graph based anomaly detection and description: a survey. Data Mining and Knowledge Discovery, 29(3), 626-688. doi:10.1007/s10618-014-0365-yUnsupervised Profiling Methods for Fraud Detection. Unpublishedhttps://www.semanticscholar.org/paper/Unsupervised-Profiling-Methods-for-Fraud-Detection-Bolton-Hand/5b640c367ae9cc4bd072006b05a3ed7c2d5f496dGao, X., Xiao, B., Tao, D., & Li, X. (2009). A survey of graph edit distance. Pattern Analysis and Applications, 13(1), 113-129. doi:10.1007/s10044-008-0141-yWhiting, D. G., Hansen, J. V., McDonald, J. B., Albrecht, C., & Albrecht, W. S. (2012). MACHINE LEARNING METHODS FOR DETECTING PATTERNS OF MANAGEMENT FRAUD. Computational Intelligence, 28(4), 505-527. doi:10.1111/j.1467-8640.2012.00425.xNgai, E. W. T., Hu, Y., Wong, Y. H., Chen, Y., & Sun, X. (2011). The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature. Decision Support Systems, 50(3), 559-569. doi:10.1016/j.dss.2010.08.00

Agricultural market dynamics based on data evidence

The final objective of this research is to characterise the evolution of agricultural products and their commercial supply through existing data. A systematic protocol for downloading data from several sources generates a sufficient mass of information to automatically establish analysis parameters. The chosen research case is coffee, and the sources used so far are AGRELMA, ALIBABA and TWITTER. The structured data of marketplaces allows to identify: producers, traders, countries, prices, sales conditions... The analysis of structured and textual data from social networks reveals: the most active accounts, the relevant topics, the relationships between market players... The relationship between the two sources will make it possible to characterise the dynamics of the coffee market and to build the actors' real profiles. Providing current, reliable and sustainable/automated data is essential for verifying the information that is transmitted and for political or economic decision-making. This research aims to build a monitoring and analysis KPI tool and to publish the results in the framework of the DATAUSE project

Detección y prevención de las malas prácticas y la corrupción desde la perspectiva de las matemáticas

[EN] In this article reference is made to the possible use of mathematical tools in the prevention and detection of fraud. The detection of fraud is considered one of the biggest challenges for public administrations. Beyond the processes of inspection and auditing, society not only requires of its administrators the prosecution of the crime but also its prevention, to avoid not only the economic damage, but also the high price that in terms of lack of services end up paying citizens, who have previously fulfilled their obligations by contributing to public coffers.[ES] En este artículo se hace referencia a la posible utilización de herramientas matemáticas en la prevención y detección del fraude. La detección del fraude se plantea como uno de los mayores desafíos de las administraciones públicas. Más allá de los procesos de inspección y auditoría, la sociedad no sólo exige de sus administradores la persecución del delito sino también su prevención, para evitar, no sólo el daño económico, sino también el alto precio que en términos de carencia de servicios acaban pagando los ciudadanos, quienes previamente han cumplido con sus obligaciones contribuyendo a las arcas públicas.Calabuig, JM.; Falciani, H.; Ferrer Sapena, A.; García-Raffi, LM.; Raso, E.; Sánchez Del Toro, I.; Sánchez Pérez, EA. (2018). Detección y prevención de las malas prácticas y la corrupción desde la perspectiva de las matemáticas. Revista Internacional de Transparencia e Integridad. (8):1-8. http://hdl.handle.net/10251/123867S18

Ciberseguridad : el reto del siglo XXI

El siglo XXI es el siglo del dato, su análisis y de la conectividad; en definitiva, el siglo de la información en tiempo real y disponible para cualquiera en cualquier lugar del mundo. Dichos datos están impactando en todos los ámbitos de la sociedad y de la economía de tal forma que no se entiende ningún sector productivo ni ninguna relación social sin dato; todos tenemos algún lugar en las redes sociales desde donde intercambiamos experiencias personales o profesionales. Si a este hecho se le suma el auge de la Inteligencia Artificial, se tiene un siglo en el que los avances tecnológicos van a ser totalmente disruptivos para todos nosotros

Hacia nuevos modelos de comunicación científica. Sciechain: propuesta para la revalorización del trabajo científico basada en tecnología blockchain

Póster presentado en las XVIII Jornadas Nacionales de Documentación Médica, celebradas en Santander (España) del 15 al 18 de junio de 2018.Ministerio de Economía y Competitividad CSO2015-65594-C2-1-R CSO2015-65594-C2-2-