We present an analysis on the uptake of open access on COVID-8 19 related literature as well as the social media attention they gather when 9 compared with non OA papers. We use a dataset of publications curated by 10 Dimensions and analyze articles and preprints. Our sample includes 11,686 11 publications of which 67.5% are openly accessible. OA publications tend to re-12 ceive the largest share of social media attention as measured by the Altmetric 13Attention Score. 37.6% of OA publications are bronze, which means toll jour-14 nals are providing free access. MedRxiv contributes to 36.3% of documents in 15 repositories but papers in BiorXiv exhibit on average higher AAS. We predict 16 the growth of COVID-19 literature in the following 30 days estimating ARIMA 17 models for the overall publications set, OA vs. non OA and by location of the 18 document (repository vs. journal). We estimate that COVID-19 publications 19 will double in the next 20 days, but non OA publications will grow at a higher 20 rate than OA publications. We conclude by discussing the implications of such 21 findings on the dissemination and communication of research findings to mit-22 igate the coronavirus outbreak.23
Abstract-Interest in hybrid methods that combine artificial neural networks (ANNs) and evolutionary algorithms (EAs) has grown in the last few years, due to their robustness and ability to design networks by setting initial weight values, by searching the architecture and the learning rule and parameters. However, papers describing the way genetic operators are tested to determine their effectiveness are scarce; moreover, few researchers publish the most suitable values of these operator parameters to solve a given problem. This paper presents an exhaustive analysis of the G-Prop method, and the different parameters the method requires (population size, selection rate, initial weight range, number of training epochs, etc.) are determined. The paper also the discusses the influence of the application of genetic operators on the precision (classification ability or error) and network size in classification problems. When making a detailed statistical analysis of the influence of each parameter, the designer should pay most attention to the parameter presenting values that are statistically most significant. The significance and relative importance of the parameters with respect to the results obtained, as well as suitable values for each, were obtained using ANalysis Of the VAriance (ANOVA). Experiments show the significance of parameters concerning the neural network and learning in the hybrid methods. Combining evolutionary algorithms and neural network learning methods can lead to better results than using those methods alone. Moreover, making the network initial weights evolve is an important factor in the process. The parameters found using this method were used to compare the G-Prop method both to itself with other parameter settings, and to other published methods.Index Terms-ANalysis Of the VAriance (ANOVA), artificial neural networks (ANNs), evolutionary algorithms (EAs), hybrid methods, optimization, statistical analysis.
Online services depend primarily on customer feedback and communications. When this kind of input is lacking, the overall approach of the service provider can shift in unintended ways. These services rely on feedback to maintain consumer satisfaction. Online social networks are a rich source of consumer data related to services and products. Well developed methods like sentiment analysis can offer insightful analyses and aid service providers in predicting outcomes based on their reviews-which, in turn, enables decision-makers to develop effective strategic plans. However, gathering this data is more challenging on Arabic online social networks, due to the complexity of the Arabic language and its dialects. In this study, we propose an approach to sentiment analysis that combines a neutrality detector model with eXtreme Gradient Boosting and a genetic algorithm to effectively predict and analyze customers' opinions of an e-Payment service through an Arabic social network. The proposed approach yields excellent results compared to other approaches. Feature analysis is also conducted on consumer reviews to identify influencing keywords.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.