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We validate the ACM-augmented baselines with 10 real-world node classification tasks. ... Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using the graph structures based on the relational inductive bias (homophily assumption). ... Combining graph signal processing and convolutional neural networks  , numerous Graph Neural Networks (GNNs) [34, 9, 15, 35, 18, 28] have been proposed which empirically outperform traditional neural ...arXiv:2109.05641v1 fatcat:nhgxphswevd3zlcy5ykejt33ha
Most computational approaches in this field are limited to the independent use of textual elements of a user's posts from social factors such as homophily and network structure. ... Stance detection refers to the task of identifying a viewpoint as either supporting or opposing a given topic. ... web domains for each of the users in our dataset in the three networks: IN, PN and CN to ensure that their similar performance is not the reason for their high similarity in their nodes. ...doi:10.7488/era/1606 fatcat:nt7t6s52gffjdpzy7rjo6nvf74
Throughout the thesis we use a network as an abstraction for a population, with vertices representing individuals in the population and edges specifying who can interact with whom. ... networks. iv DEDICATION To my aunts Subbalakshmi and Vasantha for nurturing me with care and affection, and my parents Inthumathi and Raghunathan and brother Shiva for all their support. v ACKNOWLEDGEMENTS ... Γ neural , for example, is a simple, unweighted network. A planar network is a network in which the vertices can be arranged on a plane in such a manner that the edges do not cross. ...fatcat:p4qp6nsujjdeljnvuzz3wplx3u