26,32,33,34,35,36,37. However, these works suggest that their roles regarding different types of online content vary. For example, the spreading of news has been found to be promoted by positive sentiment26,34, whereas the diffusion of health-related content is driven by negative...
(kD+kdDud)−kdEuEud(5)∂tude=Dde∇ν2ude+kdEuEud−kdeude,with nonlinear reactive boundary conditions stating that the reactions equal the flux onto (−) and off (+) the membrane(6)DD∇μuDT|μ=μ0=−uDT(kD+kdDud)(7)DD∇μuDD|μ=μ0=kdeude(8)DE∇μuE|μ=μ0=...
normativetrainingsubset. Next, for each brain region (j), we used gaussian process regression (GPR) to predict cortical volume values from age and sex using the training subset (see ref.28for details). An advantage of this approach is that in addition to fitting potentially nonlinear predictions...
Conclusions and Relevance Gunshot violence follows an epidemic-like process of social contagion that is transmitted through networks of people by social interactions. Violence prevention efforts that account for social contagion, in addition to demographics, have the potential to prevent more shootings than...
False rumors (often termed “fake news”) on social media pose a significant threat to modern societies. However, potential reasons for the widespread diffusion of false rumors have been underexplored. In this work, we analyze whether sentiment words, as
The same scheme can be applied to other scientific problems. One way of modelling a given process is by fitting a machine learning model to the data it produces. Ideally, we would like the model to be flexible enough to capture all predictable patterns. At the same time, we want it to ...
The model is interpretable because it is small and basic enough to be completely comprehended. Ideally, the user should understand the learning process well enough to realize how it forms the decision limits from the training data and why the model has these rules [5]. For ordinary users, ...
Figure 2 shows the architecture of our explanatory process and the mining of the sub-trajectory correlation, which comprises two parts: data processing and model training, and maximum explainability coverage. The first part generates the flow tensor G and the trajectory flow tensor T in Defination ...