Political misinformation, often called “fake news”, represents a threat to our democracies because it impedes citizens from being appropriately informed. Evidence suggests that fake news spreads more rapidly than real news—especially when it contains political content. The present article tests three competing theoretical accounts that have been proposed to explain the rise and spread of political (fake) news: (1) the ideology hypothesis— people prefer news that bolsters their values and worldviews; (2) the confirmation bias hypothesis—people prefer news that fits their pre-existing stereotypical knowledge; and (3) the political identity hypothesis—people prefer news that allows their political in-group to fulfill certain social goals. We conducted three experiments in which American participants read news that concerned behaviors perpetrated by their political in-group or out-group and measured the extent to which they believed the news (Exp. 1, Exp. 2, Exp. 3), and were willing to share the news on social media (Exp. 2 and 3). Results revealed that Democrats and Republicans were both more likely to believe news about the value-upholding behavior of their in-group or the value-undermining behavior of their out-group, supporting a political identity hypothesis. However, although belief was positively correlated with willingness to share on social media in all conditions, we also found that Republicans were more likely to believe and want to share apolitical fake new. We discuss the implications for theoretical explanations of political beliefs and application of these concepts in in polarized political system.
ObjectivesEchocardiographic (echo) screening is an important tool to estimate rheumatic heart disease (RHD) prevalence, but the natural history of screen-detected RHD remains unclear. The PROVAR+ (Programa de RastreamentO da VAlvopatia Reumática) study, which uses non-experts, telemedicine and portable echo, pioneered RHD screening in Brazil. We aimed to assess the mid-term evolution of Brazilian schoolchildren (5–18 years) with echocardiography-detected subclinical RHD and to assess the performance of a simplified score consisting of five components of the World Heart Federation criteria, as a predictor of unfavourable echo outcomes.SettingPublic schools of underserved areas and private schools in Minas Gerais, southeast Brazil.ParticipantsA total of 197 patients (170 borderline and 27 definite RHD) with follow-up of 29±9 months were included. Median age was 14 (12–16) years, and 130 (66%) were woman. Only four patients in the definite group were regularly receiving penicillin.Primary and secondary outcome measuresUnfavourable outcome was based on the 2-year follow-up echo, defined as worsening diagnostic category, remaining with mild definite RHD or development/worsening of valve regurgitation/stenosis.ResultsAmong patients with borderline RHD, 29 (17.1%) progressed to definite, 49 (28.8%) remained stable, 86 (50.6%) regressed to normal and 6 (3.5%) were reclassified as other heart diseases. Among those with definite RHD, 13 (48.1%) remained in the category, while 5 (18.5%) regressed to borderline, 5 (18.5%) regressed to normal and 4 (14.8%) were reclassified as other heart diseases. The simplified echo score was a significant predictor of RHD unfavourable outcome (HR 1.197, 95% CI 1.098 to 1.305, p<0.001).ConclusionThe simple risk score provided an accurate prediction of RHD status at 2-year follow-up, showing a good performance in Brazilian schoolchildren, with a potential value for risk stratification and monitoring of echocardiography-detected RHD.
The increase in wood consumption has led to the search for species that guarantee a volume of production and the least possible environmental impact. It, therefore, becomes necessary to investigate the reason behind consumer choices for certain types of wood. The designer is essential in this interpretation of reasons that lead the user to opt for a product, transforming subjective preferences into tangible design characteristics. This article presents research that investigated users' tactile and visual perceptions of wood. Tests with users, based on sensory analysis proved to be an appropriate method to study the relationship between people's subjective judgment and the technical characteristics of the products. The outcome of this study reveals the possibility of further investigations concerning the perceived aspects of users, which can add value to planted forest timber. PRACTICAL APPLICATIONSThe outcome of this study reveals the possibility of further investigations concerning the perceived aspects of users' choice when analyzing wood samples, adding value to planted forest timber. Tests with users to explore liking and their relation with attribute tests with experts are important in understanding user preferences and in investigation of user choices of certain types of wood. Through this it is possible to guide the product development. Designers are essential in this interpretation of reasons of user's choice, transforming subjective preferences into product tangible characteristics. Relating physical and hedonic aspects allows for the enhancement of product design, and the preference map allows for the guidance of the comprehension of this analysis. The preference map analysis is possible using quantitative data from the material researched.
Reputation is the opinion of the public toward a person, a group of people, or an organization. Reputation systems are particularly important in e-markets, where they help buyers to decide whether to purchase a product or not. Since a higher reputation means more profit, some users try to deceive such systems to increase their reputation. E-markets should protect their reputation systems from attacks in order to maintain a sound environment. This work addresses the task of finding attempts to deceive reputation systems in e-markets. Our goal is to generate a list of users (sellers) ranked by the probability of fraud. Firstly we describe characteristics related to transactions that may indicate frauds evidence and they are expanded to the sellers. We describe results of a simple approach that ranks sellers by counting characteristics of fraud. Then we incorporate characteristics that cannot be used by the counting approach, and we apply logistic regression to both, improved and not improved. We use real data from a large Brazilian e-market to train and evaluate our methods and the improved set with logistic regression performs better, specially when we apply stepwise optimization. We validate our results with specialists of fraud detection in this market place. In the end, we increase by 112% the number of identified fraudsters against the reputation system. In terms of ranking, we reach 93% of average precision after specialists' review in the list that uses Logistic Regression and Stepwise optimization. We also detect 55% of fraudsters with a precision of 100%.
Due to the increasing amount of information being stored and accessible through the Web, Automatic Document Classification (ADC) has become an important research topic. ADC usually employs a supervised learning strategy, where we first build a classification model using pre-classified documents and then use it to classify unseen documents. One major challenge in building classifiers is dealing with the temporal evolution of the characteristics of the documents and the classes to which they belong. However, most of the current techniques for ADC do not consider this evolution while building and using the models. Previous results show that the performance of classifiers may be affected by three different temporal effects (class distribution, term distribution and class similarity). Further, it is shown that using just portions of the pre-classified documents, which we call contexts, for building the classifiers, result in better performance, as a consequence of the minimization of the aforementioned effects.In this paper we define the concept of temporal contexts as being the portions of documents that minimize those effects. We then propose a general algorithm for determining such contexts, discuss its implementation-related issues, and propose a heuristic that is able to determine temporal contexts efficiently. In order to demonstrate the effectiveness of our strategy, we evaluated it using two distinct collections: ACM-DL and MedLine. We initially evaluated the reduction in terms of both the effort to build a classifier and the entropy associated with each context. Further, we evaluated whether these observed reductions translate into better classification performance by employing a very simple classifier, majority voting. The results show that we achieved precision gains of up to 30% compared to a version that is not temporally contextualized, and the same accuracy of a state-of-the-art classifier (SVM), while presenting an execution time up to hundreds of times faster.
IntroductionA novel handheld dual-electrode stick is a portable atrial fibrillation (AF) screening device (AFSD). We evaluated AFSD performance in primary care patients referred for echocardiogram (echo).MethodsThe AFSD has a light indication of irregular rhythm and single-lead ECG recording. Patients were instructed to hold the device for 1 min, and AF indication was recorded. A 12-lead ECG was performed for all AFSD-positive patients and 250 patients with negative AFSD screen. Echos were performed based on a clinical risk score: all high-risk patients and a sampling of low-risk patients underwent complete echo. Intermediate risk patients first had a screening echocardiogram, with a follow-up complete study if abnormality was suspected.ResultsIn 5 days, 1518 patients underwent clinical evaluation and cardiovascular risk stratification: mean age 58±16 years, 66% women. The AFSD was positive in 6.4%: 12.6% high risk, 6.1% intermediate risk and 2.2% low risk. Older age was a risk factor (9.3% vs 4.8% in those more than and less than 65 years, p=0.001). AFSD positive was independently associated with heart disease in echo (OR=3.9, 95% CI 2.1 to 7.2, p<0.001). Compared with 12-lead ECG, the AFSD had sensitivity of 90.2% (95% CI 77.0% to 97.3%) and specificity of 84.0% (95% CI 79.3% to 88.0%) for AF detection.ConclusionAFSD demonstrated high sensitivity for AF detection in primary care patients referred for echo. AF prevalence was substantial and independently associated with structural or functional heart disease, suggesting that AFSD screening could be a useful primary care tool to stratify risk and prioritise echo.
On behalf of the PROVAR (Programa de RastreamentO da VAlvopatia Reumática e outras Doenças Cardiovasculares) investigators
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