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Complex spreading phenomena in social systems = influence and contagion in real-world social networks /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Complex spreading phenomena in social systems/ edited by Sune Lehmann, Yong-Yeol Ahn.
Reminder of title:	influence and contagion in real-world social networks /
other author:	Lehmann, Sune.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	vi, 361 p. :digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	System analysis. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-77332-2
ISBN:	9783319773322

Complex spreading phenomena in social systems = influence and contagion in real-world social networks /
Complex spreading phenomena in social systemsinfluence and contagion in real-world social networks /[electronic resource] :edited by Sune Lehmann, Yong-Yeol Ahn. - Cham :Springer International Publishing :2018. - vi, 361 p. :digital ;24 cm. - Computational social sciences,2509-9574. - Computational social sciences..

Part 1: Introduction to spreading in social systems -- Complex contagions: A decade in review -- A simple person's approach to understanding the contagion condition for spreading processes on generalized random networks -- Challenges to estimating contagion effects from observational data -- Part 2: Models and Theories -- Slightly generalized Generalized Contagion: Unifying simple models of biological and social spreading -- Message-passing methods for complex contagions -- Optimal modularity in complex contagion -- Probing empirical contact networks by simulation of spreading dynamics -- Theories for influencer identification in complex networks -- Part 3: Observational studies -- Service adoption spreading in online social networks -- Misinformation spreading on Facebook -- Scalable detection of viral memes from diffusion patterns -- Attention on weak ties in social and communication networks -- Measuring social spam and the effect of bots on information diffusion in social media -- Network happiness: how online social interactions relate to our well being -- Information spreading during emergencies and anomalous events -- Part 4: Controlled studies -- Randomized Experiments to detect and estimate social influence -- The rippling effect of social influence via phone communication network -- Network experiments through academic-industry collaboration -- Spreading in Social Systems: Reflections.

This text is about spreading of information and influence in complex networks. Although previously considered similar and modeled in parallel approaches, there is now experimental evidence that epidemic and social spreading work in subtly different ways. While previously explored through modeling, there is currently an explosion of work on revealing the mechanisms underlying complex contagion based on big data and data-driven approaches. This volume consists of four parts. Part 1 is an Introduction, providing an accessible summary of the state-of-the-art. Part 2 provides an overview of the central theoretical developments in the field. Part 3 describes the empirical work on observing spreading processes in real-world networks. Finally, Part 4 goes into detail with recent and exciting new developments: dedicated studies designed to measure specific aspects of the spreading processes, often using randomized control trials to isolate the network effect from confounders, such as homophily. Each contribution is authored by leading experts in the field. This volume, though based on technical selections of the most important results on complex spreading, remains quite accessible to the newly interested. The main benefit to the reader is that the topics are carefully structured to take the novice to the level of expert on the topic of social spreading processes. This book will be of great importance to a wide field: from researchers in physics, computer science, and sociology to professionals in public policy and public health.

ISBN: 9783319773322

Standard No.: 10.1007/978-3-319-77332-2doiSubjects--Topical Terms:

528439
System analysis.

LC Class. No.: QA402 / .C667 2018

Dewey Class. No.: 003

Complex spreading phenomena in social systems = influence and contagion in real-world social networks /
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245 0 0 $a Complex spreading phenomena in social systems $h [electronic resource] : $b influence and contagion in real-world social networks / $c edited by Sune Lehmann, Yong-Yeol Ahn.
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490 1 $a Computational social sciences, $x 2509-9574
505 0 $a Part 1: Introduction to spreading in social systems -- Complex contagions: A decade in review -- A simple person's approach to understanding the contagion condition for spreading processes on generalized random networks -- Challenges to estimating contagion effects from observational data -- Part 2: Models and Theories -- Slightly generalized Generalized Contagion: Unifying simple models of biological and social spreading -- Message-passing methods for complex contagions -- Optimal modularity in complex contagion -- Probing empirical contact networks by simulation of spreading dynamics -- Theories for influencer identification in complex networks -- Part 3: Observational studies -- Service adoption spreading in online social networks -- Misinformation spreading on Facebook -- Scalable detection of viral memes from diffusion patterns -- Attention on weak ties in social and communication networks -- Measuring social spam and the effect of bots on information diffusion in social media -- Network happiness: how online social interactions relate to our well being -- Information spreading during emergencies and anomalous events -- Part 4: Controlled studies -- Randomized Experiments to detect and estimate social influence -- The rippling effect of social influence via phone communication network -- Network experiments through academic-industry collaboration -- Spreading in Social Systems: Reflections.
520 $a This text is about spreading of information and influence in complex networks. Although previously considered similar and modeled in parallel approaches, there is now experimental evidence that epidemic and social spreading work in subtly different ways. While previously explored through modeling, there is currently an explosion of work on revealing the mechanisms underlying complex contagion based on big data and data-driven approaches. This volume consists of four parts. Part 1 is an Introduction, providing an accessible summary of the state-of-the-art. Part 2 provides an overview of the central theoretical developments in the field. Part 3 describes the empirical work on observing spreading processes in real-world networks. Finally, Part 4 goes into detail with recent and exciting new developments: dedicated studies designed to measure specific aspects of the spreading processes, often using randomized control trials to isolate the network effect from confounders, such as homophily. Each contribution is authored by leading experts in the field. This volume, though based on technical selections of the most important results on complex spreading, remains quite accessible to the newly interested. The main benefit to the reader is that the topics are carefully structured to take the novice to the level of expert on the topic of social spreading processes. This book will be of great importance to a wide field: from researchers in physics, computer science, and sociology to professionals in public policy and public health.
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