scholarly journals Erratum to Online Social Networks and information diffusion: The role of ego networks: Online Social Networks and Media, Volume 1 (June 2017), Pages 44-55

2022 ◽  
Vol 27 ◽  
pp. 100184
Author(s):  
Valerio Arnaboldi ◽  
Marco Conti ◽  
Andrea Passarella ◽  
Robin I.M. Dunbar
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Ego Networks ◽  
Media Volume

scholarly journals Online Social Networks and information diffusion: The role of ego networks

2017 ◽  
Vol 1 ◽  
pp. 44-55 ◽  
Author(s):  
Valerio Arnaboldi ◽  
Marco Conti ◽  
Andrea Passarella ◽  
Robin I.M. Dunbar
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Ego Networks

Subtle role of latency for information diffusion in online social networks

2016 ◽  
Vol 25 (10) ◽  
pp. 108904 ◽  
Author(s):  
Fei Xiong ◽  
Xi-Meng Wang ◽  
Jun-Jun Cheng
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Information Diffusion

Influence and Information Flow in Online Social Networks

2017 ◽  
Vol 9 (4) ◽  
pp. 1-17
Author(s):  
Afrand Agah ◽  
Mehran Asadi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Large Data ◽  
Marketing Strategies ◽  
Large Data Sets ◽  
Divide And Conquer ◽  
Data Sets ◽  
Divide And Conquer Algorithm ◽  
Flow Of Information

This article introduces a new method to discover the role of influential people in online social networks and presents an algorithm that recognizes influential users to reach a target in the network, in order to provide a strategic advantage for organizations to direct the scope of their digital marketing strategies. Social links among friends play an important role in dictating their behavior in online social networks, these social links determine the flow of information in form of wall posts via shares, likes, re-tweets, mentions, etc., which determines the influence of a node. This article initially identities the correlated nodes in large data sets using customized divide-and-conquer algorithm and then measures the influence of each of these nodes using a linear function. Furthermore, the empirical results show that users who have the highest influence are those whose total number of friends are closer to the total number of friends of each node divided by the total number of nodes in the network.

Information Diffusion in Social Networks

2011 ◽  
pp. 146-163 ◽  
Author(s):  
Dmitry Zinoviev
Keyword(s):  
Social Networks ◽  
Information Flow ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Diffusion Processes ◽  
Small World ◽  
The Social ◽  
Strength Of Weak Ties ◽  
Strategic Position

The issue of information diffusion in small-world social networks was first systematically brought to light by Mark Granovetter in his seminal paper “The Strength of Weak Ties” in 1973 and has been an area of active academic studies in the past three decades. This chapter discusses information proliferation mechanisms in massive online social networks (MOSN). In particular, the following aspects of information diffusion processes are addressed: the role and the strategic position of influential spreaders of information; the pathways in the social networks that serve as conduits for communication and information flow; mathematical models describing proliferation processes; short-term and long-term dynamics of information diffusion, and secrecy of information diffusion.

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