![]() In this paper, we propose a new framework for understanding this reversing effect. However, the opposite question, i.e., how does information diffusion process rebuild social networks, has been largely ignored. It is widely believed that social networks play important role in the process of information diffusion. In this big data era, more and more social activities are digitized thereby becoming traceable, and thus the studies of social networks attract increasing attention from academia. The chapter is an effort in the direction of online social network analysis that explores the basic methods that can be process and analyze the network with a suitable approach to yield knowledge. Local features include properties of nodes like degree of the node (in-degree, out-degree) while global feature process the path between nodes in the entire network. This is referred to as social network analysis, and the features exploited usually are local and global both plays significant role in processing and computation. Processing of online social networks structural features yields fair knowledge which can be used in many of recommendation and prediction systems. The structure of social networks is comprised of nodes and edges whereas users are entities represented by node and relationships designated by edges. Millions of users are appending to it and enriching the nature and behavior, and the information generated has various dimensional properties providing new opportunities and perspective for computation of network properties. Finally, we present two use cases that can highly benefit from the knowledge on k-bridges detected through our approach.Įxpansion of online social networks is rapid and furious. We also propose two further specializations of k-bridges, regarding Reddit and the network of patent inventors, to prove that the knowledge on k-bridges we initially found in Yelp is not limited to this social network. In addition, we investigate the relationship between k-bridges and the main centrality measures in the macro-categories of Yelp. We also analyze the relationship between k-bridges and power users. Then, we verify if there exists an influence exerted by k-bridges on their friends and/or on their co-reviewers. In particular, we investigate how some basic characteristics of Yelp k-bridges vary against k (i.e., against the number of macro-categories which the businesses reviewed by them belong to). Then, we analyze the specialization of this concept and algorithm in Yelp and we extract several knowledge patterns about Yelp k-bridges. Their thin, shrill voices rose high above the roar of the flames and the crash of the masonry, like the yelping of a pack of wolves who see their quarry before them and know that they have well-nigh run him down.In this paper, we introduce the concept of k-bridge (i.e., a user who connects k sub-networks of the same network or k networks of a multi-network scenario) and propose an algorithm for extracting k-bridges from a social network. Then she could not endure the dog, a fat, cross beast who snarled and yelped at her when she made his toilet, and who lay on his back with all his legs in the air and a most idiotic expression of countenance when he wanted something to eat, which was about a dozen times a day. (The Lost World, by Sir Arthur Conan Doyle) The Indian looked up at him, and then, with a little yelp, cringed to the ground and clung to Lord John's leg. Seward's house by the yelping of dogs, and after about a minute three terriers came dashing round the corner of the house. (Rodney Stone, by Sir Arthur Conan Doyle) ![]() Pilot pricked up his ears when I came in: then he jumped up with a yelp and a whine, and bounded towards me: he almost knocked the tray from my hands.Īnd so those two brave-hearted fellows made their way amidst the yelping roughs, like two wounded lions amidst a pack of wolves and jackals. (Love of Life and Other Stories, by Jack London) Often their yelps drifted across the desolation, and once he saw three of them slinking away before his path. And with every rock he struck, he yelped.Īs the moments passed the yelps grew closer and louder.
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