ABSTRACT
Despite echo chambers in social media have been under considerable scrutiny, general models for their detection and analysis are missing. In this work, we aim to fill this gap by proposing a probabilistic generative model that explains social media footprints - -i.e., social network structure and propagations of information - -through a set of latent communities, characterized by a degree of echo-chamber behavior and by an opinion polarity. Specifically, echo chambers are modeled as communities that are permeable to pieces of information with similar ideological polarity, and impermeable to information of opposed leaning: this allows discriminating echo chambers from communities that lack a clear ideological alignment. To learn the model parameters we propose a scalable, stochastic adaptation of the Generalized Expectation Maximization algorithm, that optimizes the joint likelihood of observing social connections and information propagation. Experiments on synthetic data show that our algorithm is able to correctly reconstruct ground-truth latent communities with their degree of echo-chamber behavior and opinion polarity. Experiments on real-world data about polarized social and political debates, such as the Brexit referendum or the COVID-19 vaccine campaign, confirm the effectiveness of our proposal in detecting echo chambers. Finally, we show how our model can improve accuracy in auxiliary predictive tasks, such as stance detection and prediction of future propagations. © 2022 ACM.
ABSTRACT
Correct quality management can bring several benefits to the company, from reducing operating costs to increasing the number of customers. In this context, several improvements can be implemented to boost an enterprise during the Covid-19 pandemic. This article is characterized as a case study. In this study, quality assessment tools were applied as a means of proposing strategic improvements in a set of indicators to measure their quality level. The main objective of this work was to propose improvements through quality indicators to improve a company in the food sector in the seafood business. The present research is characterized as exploratory, of an applied nature and with an inductive scientific method, the technical procedure used to carry out this research was the applied case study. Based on the data and information collected during the research, it was possible to determine several quality indicators and, consequently, appropriate improvements to the studied company.
ABSTRACT
OBJECTIVES: From December 2019, a novel coronavirus disease named COVID-19 was reported in China. Within 3 months, the World Health Organization defined COVID-19 as a pandemic, with more than 370,000 cases and 16,000 deaths worldwide. In consideration of the crucial role of diagnostic testing during COVID-19, the aim of this technical note was to provide a complete synthesis of approaches implemented for the management of suspected or confirmed COVID-19 patients. KEY FINDINGS: The planning of a robust plan to prevent the transmission of the virus to patients and department staff members should be fundamental in each radiology service. Moreover, the speed of spread and the incidence of the pandemic make it necessary to optimize the use of personal protective devices and dedicated COVID-19 equipment, given the limited availability of supplies. CONCLUSION: In the management of radiographic and CT imaging, staff should take special precautions to limit contamination between patients and other patients or professionals. IMPLICATIONS FOR PRACTICE: An isolated imaging room should be dedicated to suspected or confirmed COVID-19 cases, including radiography and CT scanners. This paper will provide guidance concerning disposable protective gear to be utilized, as well as on the cleaning and sanitation of radiology room and equipment.