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SOCNET  May 2017

SOCNET May 2017

Subject:

selected not-the-Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Tue, 2 May 2017 17:02:09 -0400

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (164 lines)

*****  To join INSNA, visit http://www.insna.org  *****

Catching up because was busy a week ago

   Barry Wellman

    A vision is just a vision if it's only in your head
    Step by step, link by link, putting it together
                  Streisand/Sondheim
  _______________________________________________________________________
   NetLab Network                 FRSC                      INSNA Founder
   http://www.chass.utoronto.ca/~wellman           twitter: @barrywellman
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman
                        http://amzn.to/zXZg39
   _______________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 24 Apr 2017 11:04:40 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=8b94176e36&e=55e25a0e3e



Exercise contagion in a global social network

    http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=667adb776b&e=55e25a0e3e

We leveraged exogenous variation in weather patterns across geographies to identify social contagion in exercise behaviours across a global social network. We estimated these contagion effects by combining daily global weather data, which creates exogenous variation in running among friends, with data on the network ties and daily exercise patterns of ˙˙1.1M individuals who ran over 350M˙˙km in a global social network over 5 years. Here we show that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends. Less active runners influence more active runners, but not the reverse. Both men and women influence men, while only women influence other women. While the Embeddedness and Structural Diversity theories of social contagion explain the influence effects we observe, the Complex Contagion theory does not. These results suggest interventions that account for social contagion will spread behaviour
change more effectively.

BW: A lovely papr


Exercise contagion in a global social network
Sinan Aral & Christos Nicolaides
Nature Communications 8, Article number: 14753 (2017)
doi:10.1038/ncomms14753

Source: www.nature.com (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=67f22e9882&e=55e25a0e3e)


Cumulative culture can emerge from collective intelligence in animal groups

    http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=22260b8504&e=55e25a0e3e

Studies of collective intelligence in animal groups typically overlook potential improvement through learning. Although knowledge accumulation is recognized as a major advantage of group living within the framework of Cumulative Cultural Evolution (CCE), the interplay between CCE and collective intelligence has remained unexplored. Here, we use homing pigeons to investigate whether the repeated removal and replacement of individuals in experimental groups (a key method in testing for CCE) alters the groups˙˙ solution efficiency over successive generations. Homing performance improves continuously over generations, and later-generation groups eventually outperform both solo individuals and fixed-membership groups. Homing routes are more similar in consecutive generations within the same chains than between chains, indicating cross-generational knowledge transfer. Our findings thus show that collective intelligence in animal groups can accumulate progressive modifications
over time. Furthermore, our results satisfy the main criteria for CCE and suggest potential mechanisms for CCE that do not rely on complex cognition.


Cumulative culture can emerge from collective intelligence in animal groups
Takao Sasaki & Dora Biro
Nature Communications 8, Article number: 15049 (2017)
doi:10.1038/ncomms15049

Source: www.nature.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=410759f7f6&e=55e25a0e3e)



Universal Scaling Laws in Metro Area Election Results

    We explain the anomaly of election results between large cities and 
rural areas in terms of urban scaling in the 1948-2016 US elections and in 
the 2016 EU referendum of the UK. The scaling curves are all universal and 
depend on a single parameter only, and one of the parties always shows 
superlinear scaling and drives the process, while the sublinear exponent 
of the other party is merely the consequence of probability conservation. 
Based on the recently developed model of urban scaling, we give a 
microscopic model of voter behavior in which we replace diversity 
characterizing humans in creative aspects with social diversity and 
tolerance. The model can also predict new political developments such as 
the fragmentation of the left and 'the immigration paradox'.


Universal Scaling Laws in Metro Area Election Results

Eszter Bokányi, Zoltán Szállási, Gábor Vattay

Source: arxiv.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a7a7f14460&e=55e25a0e3e)



The evolution of extreme cooperation via shared dysphoric experiences

    Willingness to lay down one˙˙s life for a group of non-kin, well 
documented historically and ethnographically, represents an evolutionary 
puzzle. Building on research in social psychology, we develop a 
mathematical model showing how conditioning cooperation on previous shared 
experience can allow individually costly pro-group behavior to evolve. The 
model generates a series of predictions that we then test empirically in a 
range of special sample populations (including military veterans, college 
fraternity/sorority members, football fans, martial arts practitioners, 
and twins). Our empirical results show that sharing painful experiences 
produces ˙˙identity fusion˙˙ ˙˙ a visceral sense of oneness ˙˙ which in 
turn can motivate self-sacrifice, including willingness to fight and die 
for the group. Practically, our account of how shared dysphoric 
experiences produce identity fusion helps us better understand such 
pressing social issues as suicide terrorism, holy wars, sectarian 
violence, gang-related violence, and other forms of intergroup conflict.


The evolution of extreme cooperation via shared dysphoric experiences
Harvey Whitehouse, Jonathan Jong, Michael D. Buhrmester, Ángel Gómez, Brock Bastian, Christopher M. Kavanagh, Martha Newson, Miriam Matthews, Jonathan A. Lanman, Ryan McKay & Sergey Gavrilets

Scientific Reports 7, Article number: 44292 (2017)
doi:10.1038/srep44292

Source: www.nature.com (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7aec24225f&e=55e25a0e3e)



Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale

    Urban planning applications (energy audits, investment, etc.) require 
an understanding of built infrastructure and its environment, i.e., both 
low-level, physical features (amount of vegetation, building area and 
geometry etc.), as well as higher-level concepts such as land use classes 
(which encode expert understanding of socio-economic end uses). This kind 
of data is expensive and labor-intensive to obtain, which limits its 
availability (particularly in developing countries). We analyze patterns 
in land use in urban neighborhoods using large-scale satellite imagery 
data (which is available worldwide from third-party providers) and 
state-of-the-art computer vision techniques based on deep convolutional 
neural networks. For supervision, given the limited availability of 
standard benchmarks for remote-sensing data, we obtain ground truth land 
use class labels carefully sampled from open-source surveys, in particular 
the Urban Atlas land classification dataset of 20 land use classes across 
300 European cities. We use this data to train and compare deep 
architectures which have recently shown good performance on standard 
computer vision tasks (image classification and segmentation), including 
on geospatial data. Furthermore, we show that the deep representations 
extracted from satellite imagery of urban environments can be used to 
compare neighborhoods across several cities. We make our dataset available 
for other machine learning researchers to use for remote-sensing 
applications.


Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale
Adrian Albert, Jasleen Kaur, Marta Gonzalez

Source: arxiv.org (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=436fcd1985&e=55e25a0e3e)


==============================================
Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

You can contribute to Complexity Digest selecting one of our topics (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b605b7273a&e=55e25a0e3e ) and using the "Suggest" button.
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