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Barry Wellman, FRSC               Director, NetLab Network
Founder, International Network for Social Network Analysis

Kyle Lowry is My Spirit Animal
Step by step, link by link, putting it together--Streisand/Sondheim
The earth to be spannd, connected by network--Walt Whitman
It's Always Something--Roseanne Roseannadanna
A day like all days, filled with those events that alter and illuminate our times--You Are There!

NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman    

-------- Forwarded Message --------
Subject: 	Latest Complexity Digest Posts
Date: 	Mon, 10 Feb 2020 12:03:05 +0000
From: 	Complexity Digest <[log in to unmask]>
Reply-To: 	[log in to unmask]
To: 	Barry <[log in to unmask]>

Learn about the latest and greatest related to complex systems research. 
More at 

Friendship paradox biases perceptions in directed networks

Nazanin Alipourfard, Buddhika Nettasinghe, Andrés Abeliuk, Vikram 
Krishnamurthy & Kristina Lerman
Nature Communications volume 11, Article number: 707 (2020)

Social networks shape perceptions by exposing people to the actions and 
opinions of their peers. However, the perceived popularity of a trait or 
an opinion may be very different from its actual popularity. We 
attribute this perception bias to friendship paradox and identify 
conditions under which it appears. We validate the findings empirically 
using Twitter data. Within posts made by users in our sample, we 
identify topics that appear more often within users’ social feeds than 
they do globally among all posts. We also present a polling algorithm 
that leverages the friendship paradox to obtain a statistically 
efficient estimate of a topic’s global prevalence from biased individual 
perceptions. We characterize the polling estimate and validate it 
through synthetic polling experiments on Twitter data. Our paper 
elucidates the non-intuitive ways in which the structure of directed 
networks can distort perceptions and presents approaches to mitigate 
this bias.

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Multilayer modeling of adoption dynamics in energy demand management

Chaos 30, 013153 (2020); 
Iacopo Iacopini, Benjamin Schäfer, Elsa Arcaute, Christian Beck, and 
Vito Latora

The electricity system is in the midst of large transformations, and new 
business models have emerged quickly to facilitate new modes of 
operation of the electricity supply. The so-called demand response seeks 
to coordinate demand from a large number of users through incentives, 
which are usually economic such as variable pricing tariffs. Here, we 
propose a simple mathematical framework to model consumer behaviors 
under demand response. Our model considers at the same time social 
influence and customer benefits to opt into and stay within new control 
schemes. In our model, information about the existence of a contract 
propagates through the links of a social network, while the geographic 
proximity of clusters of adopters influences the likelihood of 
participation by decreasing the likelihood of opting out. The results of 
our work can help to make informed decisions in energy demand management.

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Enhanced Ability of Information Gathering May Intensify Disagreement 
Among Groups

Hiroki Sayama

Today's society faces widening disagreement and conflicts among 
constituents with incompatible views. Escalated views and opinions are 
seen not only in radical ideology or extremism but also in many other 
scenes of our everyday life. Here we show that widening disagreement 
among groups may be linked to the advancement of information 
communication technology, by analyzing a mathematical model of 
population dynamics in a continuous opinion space. We adopted the 
interaction kernel approach to model enhancement of people's information 
gathering ability and introduced a generalized non-local gradient as 
individuals' perception kernel. We found that the characteristic 
distance between population peaks becomes greater as the wider range of 
opinions becomes available to individuals or the greater attention is 
attracted to opinions distant from theirs. These findings may provide a 
possible explanation for why disagreement is growing in today's 
increasingly interconnected society, without attributing
its cause only to specific individuals or events.

( )

Antifragility Predicts the Robustness and Evolvability of Biological 
Networks through Multi-class Classification with a Convolutional Neural 

Hyobin Kim, Stalin Muñoz, Pamela Osuna, Carlos Gershenson

Robustness and evolvability are essential properties to the evolution of 
biological networks. To determine if a biological network is robust 
and/or evolvable, the comparison of its functions before and after 
mutations is required. However, it has an increasing computational cost 
as network size grows. Here we aim to develop a predictor to estimate 
the robustness and evolvability of biological networks without an 
explicit comparison of functions. We measure antifragility in Boolean 
network models of biological systems and use this as the predictor. 
Antifragility is a property to improve the capability of a system 
through external perturbations. By means of the differences of 
antifragility between the original and mutated biological networks, we 
train a convolutional neural network (CNN) and test it to classify the 
properties of robustness and evolvability. We found that our CNN model 
successfully classified the properties. Thus, we conclude that our 
antifragility measure can be used as a
significant predictor of the robustness and evolvability of biological 

( )

We are looking for a research scientist to help run the Observatory on 
Social Media (OSoMe, pronounced awe•some) at Indiana University 
Bloomington (IUB). The official title of the position is Senior Project 
Coordinator (SPC). The Senior Project Coordinator will join the OSoMe 
senior management team — director Filippo Menczer, co-directors for 
research Betsi Grabe and Alessandro Flammini, co-directors for education 
Elaine Monaghan and John Paolillo, Dean James Shahahan, and associate 
director for technology Val Pentchev. The mission of the Observatory, 
which recently received a $6 million investment from the John S. and 
James L. Knight Foundation and Indiana University, is to study the media 
and technology networks that drive the online diffusion of 
dis/mis/information. OSoMe offers access to data and tools for 
researchers worldwide to uncover the vulnerabilities of the media 
ecosystem and develops methods for increasing the resilience of citizens 
and democratic systems to manipulation.

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A First Course in Network Science 

The book A First Course in Network Science 
( ) 
by CNetS faculty members Filippo Menczer and Santo Fortunato and CNetS 
PhD graduate Clayton A. Davis was recently published by Cambridge 
University Press 
( ) 
. This textbook introduces the basics of network science for a wide 
range of job sectors from management to marketing, from biology to 
engineering, and from neuroscience to the social sciences. Extensive 
tutorials, datasets, and homework problems provide plenty of hands-on 
practice. The book has been endorsed as “Rigorous” (Alessandro 
Vespignani), “comprehensive… indispensable” (Olaf Sporns), “with 
remarkable clarity and insight” (Brian Uzzi), “accessible” 
(Albert-László Barabási), “amazing… extraordinary” (Alex Arenas), and 
“sophisticated yet introductory… an excellent introduction that is also 
eminently prac
tical” (Stephen Borgatti). It was ranked by Amazon 
( ) 
#1 among new releases in mathematical physics.

( )

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