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Diffusion of Innovations in Social Networks Based on Game Theoretic Approaches
, M.Sc. Thesis Sharif University of Technology ; Ghodsi, Mohammad (Supervisor)
Abstract
Recently, computer scientists and economists have defined many joint problems and cooperate widely in various areas. Importance of this interconnection is clear for everybody, now. New works have been conducted, nowadays, to use the daily - increasing web-based social networks in viral marketing for improving companies profits. The main problem which is proved to be NP-Complete in this context is about discovering k most influential nodes in a network. In this dissertation, we generalize the problem to a group-based version and we we use group-based advertising to achieve our main goal. A new algorithm called Group-Based Diffusion technique is proposed in this thesis for solving this problem...
Proposing a Method for Ranking Nodes in Complex Networks
, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor) ; Safaei Semnani, Farshad (Co-Supervisor)
Abstract
A distinct viewpoint is adopted by each centrality to analyze a network and rank its nodes. This study aims to introduce a novel centrality that ranks the nodes of a network more effectively. In this respect, a function of five centralities, namely betweenness, closeness, agent vector, degree, and Katz, is introduced to maximize the connected components of the network after ranking its nodes and deleting the first twenty ones. The proposed centrality functions better than the other mentioned centralities. Among the networks simulated to evaluate the centrality, it functions better in Erdos-Renyi and small-world networks, both of whom being based on the Poisson degree distribution, and...
Compressed sensing in cyber physical social systems
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume 10760 LNCS , 2018 , Pages 287-305 ; 03029743 (ISSN) ; Ghalebi, K. E ; Movaghar, A ; Mahyar, H ; Sharif University of Technology
Abstract
We overview the main results in Compressed Sensing and Social Networks, and discuss the impact they have on Cyber Physical Social Systems (CPSS), which are currently emerging on top of the Internet of Things. Moreover, inspired by randomized Gossip Protocols, we introduce TopGossip, a new compressed-sensing algorithm for the prediction of the top-k most influential nodes in a social network. TopGossip is able to make this prediction by sampling only a relatively small portion of the social network, and without having any prior knowledge of the network structure itself, except for its set of nodes. Our experimental results on three well-known benchmarks, Facebook, Twitter, and Barabási,...
Communities detection for advertising by futuristic greedy method with clustering approach
, Article Big Data ; Volume 9, Issue 1 , 2021 , Pages 22-40 ; 21676461 (ISSN) ; Izadi, M ; Sharif University of Technology
Mary Ann Liebert Inc
2021
Abstract
Community detection in social networks is one of the advertising methods in electronic marketing. One of the approaches to find communities in large social networks is to use greedy methods, because these methods perform very fast. Greedy methods are generally designed based on local decisions; thus, inappropriate local decisions may result in an improper global solution. The use of a greedy improved index with a futuristic approach can, to some extent, prevent inappropriate local choices. Our proposed method determines the influential nodes in the social network based on the followers and following and new futuristic greedy index. It classifies the nodes based on the influential nodes by...