Results 41 to 50 of about 256,683 (274)
An Influence maximization algorithm in social network using K-shell decomposition and community detection [PDF]
Network Biology, 2020 The increasing use of services and different applications of social networks has led to a wide range of research and studies in the field of information technology and computer networks towards such networks.
Alighanbari, Esmaeil Bagheri
doaj
Targeted Influence Maximization Based on Cloud Computing Over Big Data in Social Networks
IEEE Access, 2020 This paper focuses on the targeted influence maximization based on cloud computing in social networks. Most of existing influence maximization works assume that the influence diffusion probabilities on edges are fixed, and identify the Top-k users to ...
Shiyu Chen +4 more
doaj +1 more source
A new method for maximizing influence on social networks based on node membership in communities [PDF]
Network Biology, 2020 Influence maximization is one of the fundamental issues in social networks context. In viral marketing which is one of applications of this category, a small group of users are selected to accept a product and influence of these users on other people ...
Esmaeil Bagheri
doaj
Geodemographic Influence Maximization
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 Given a set of locations in a city, on which ones should we place ads on so as to reach as many people as possible within a limited budget? Past research has addressed this question under the assumption that dense trajectory data are available to determine the reach of each ad.
Zhang, Kaichen +5 more
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Influence blocking maximization under refutation
Social Network Analysis and Mining, 2023 Abstract In social networks, a phenomenon termed the refutation mechanism arises when certain users spontaneously counter negative information based on their knowledge and experience. To the best of our knowledge, this paper focuses on the influence blocking maximization under the refutation mechanism for the first time.
Qi Luo +5 more
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Influence Learning and Maximization [PDF]
, 2021 The problem of maximizing or minimizing the spreading in a social network has become more timely than ever with the advent of fake news and the coronavirus epidemic. The solution to this problem pertains to influence maximization algorithms that identify the right nodes to lockdown for epidemic containment, hire for viral marketing campaigns, block for
Panagopoulos, George +1 more
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A reliability-based approach for influence maximization using the evidence theory [PDF]
, 2017 The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation.
A Bozorgi +18 more
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Research on the Dynamic Multisocial Networks Influence Maximization Problem Based on Common Users
IEEE Access, 2021 The influence maximization problem of a single social network is to find a set of $k$ seed nodes $S$ so that the spread of information from the seed set to the single network has the largest influence. This problem has attracted the attention of many
Yanhong Meng +4 more
doaj +1 more source
Effects of Time Horizons on Influence Maximization in the Voter Dynamics
, 2018 In this paper we analyze influence maximization in the voter model with an active strategic and a passive influencing party in non-stationary settings. We thus explore the dependence of optimal influence allocation on the time horizons of the strategic ...
Brede, Markus +2 more
core +1 more source
Scalable Lattice Influence Maximization [PDF]
IEEE Transactions on Computational Social Systems, 2020 Influence maximization is the task of finding k seed nodes in a social network such that the expected number of activated nodes in the network (under certain influence propagation model), referred to as the influence spread, is maximized. Lattice influence maximization (LIM) generalizes influence maximization such that, instead of selecting k seed ...
Wei Chen, Ruihan Wu, Zheng Yu
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