***** To join INSNA, visit http://www.insna.org *****
Back from Purdue--the Hoosier Heartland as the sign said. Not one red MAGA
cap; no bumper stickers. But lots of smart, polite students and faculty.
Selected abstracts below
Barry Wellman
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--Walter Cronkite
_______________________________________________________________________
Director, NetLab Network FRSC
Distinguished Visiting Scholar Social Media Lab Ryerson University
Founder, International Network for Social Network Analysis
NETWORKED: The New Social Operating System Lee Rainie & Barry Wellman
https://urldefense.proofpoint.com/v2/url?u=http-3A__www.chass.utoronto.ca_-7Ewellman&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=U4eMOxCdbOMrHu6qsv1OqyJQOj9zbkxkdoR8K6tZJBQ&e= https://urldefense.proofpoint.com/v2/url?u=http-3A__amzn.to_zXZg39&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=yirbKJDCEb__OWGIEFwEMS1KxRFWW8RMI1BnIraIX4Y&e=
https://urldefense.proofpoint.com/v2/url?u=https-3A__en.wikipedia.org_wiki_Barry-5FWellman&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=Ocr2bGF1JV9GD0W_y_4Qss7xsomkdDhr-L_hj7fRa7w&e=
_______________________________________________________________________
---------- Forwarded message ----------
Date: Mon, 15 Apr 2019 11:04:45 +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 https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D940501a42f-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=qC70BlTLXbrCsuYGzW4mQ_UQKlSnhCDVRed1juB_2Aw&e=
Space: The Final Illusion
https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D58d8edfcd0-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=HAMM7PiI2IVOeZAHVI_If6cAKRM5-Gn2T4a7XYhR1fo&e=
(...) the takeaway lesson is that the intuitive idea that objects
influence each other because they are close in space is soon to become
another of those easy beliefs that turn out to be wrong when we look
deeper. The smoothness of space is soon to become an illusion that hides a
tiny and complex world of causal interactions, which do not live in
space˙˙but which rather define and create space as they create the future
from the present.
Source: blogs.scientificamerican.com (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D1ca4882685-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=XaWL_pRE5KadDbT5cEmAZjL8by1U1acFxnhZkEMcYX0&e=)
Modeling Small Systems Through the Relative Entropy Lattice
There are certain contexts, where we would like to analyze the behavior of small interacting systems, such as sports teams. While large interacting systems have drawn much attention in the past years, let it be physical systems of interacting particles or social networks, small systems are short of appropriate quantitative modeling and measurement tools. We propose a simple procedure for analyzing a small system through the degree in which its behavior at different granularity levels (e.g., dyads) non-linearly diverges from the simple additive behavior of its sub-units. For example, we may model the behavior of a soccer team by measuring the extent to which the behavior changes when we move from individual players to dyads, triads, and so on. In this paper, we address the challenge of modeling small systems in terms of measuring divergence from additivity at different granularity levels of the system. We present and develop a measure for quantifying divergence from additivity
through what we term a Relative Entropy Lattice , and illustrate its benefits in modeling the behavior of a specific small system, a soccer team, using data from the English Premier League. Our method has practical implications too, such as allowing the coach to identify ˙˙hidden˙˙ weak spots in the team˙˙s behavior.
Modeling Small Systems Through the Relative Entropy Lattice
Yair Neuman ; Dan Vilenchik
IEEE Access ( Volume: 7 )
Page(s): 43591 - 43597
Source: ieeexplore.ieee.org (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D03cf5252a6-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=RnaDmK1nWfK0pLjVwac_iUAz1pSgU8MC7MP929Du2eU&e=)
Temporal and spatial analysis of the media spotlight
* An earthquake in Mexico received the spotlight of the media for
several weeks, allowed quantifying media coverage. * A person from a large
city receives more attention from the media, per person, than a person
from a small city. * The coverage that the media places on a specific
event or topic has an exponential decay. The coverage given to an event
drops by half every eight days.
Temporal and spatial analysis of the media spotlight
Rafael Prieto Curiel, Carmen Cabrera Arnau, MaraTorres Pinedo, Humberto González Ramírez, Steven R.Bishop
Computers, Environment and Urban Systems
Volume 75, May 2019, Pages 254-263
Source: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.sciencedirect.com&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=AhMEYsV4YXIhwVem_w5oFCK0BOEm40Ma21eYE3YIE8Q&e= (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D27566a94f5-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=KbhVeVzJIg4bnW4thbz5oydImB8o3ZXqcYyeb_kpvbM&e=)
Hot Streaks on Social Media
Measuring the impact and success of human performance is common in
various disciplines, including art, science, and sports. Quantifying
impact also plays a key role on social media, where impact is usually
defined as the reach of a user's content as captured by metrics such as
the number of views, likes, retweets, or shares. In this paper, we study
entire careers of Twitter users to understand properties of impact. We
show that user impact tends to have certain characteristics: First, impact
is clustered in time, such that the most impactful tweets of a user appear
close to each other. Second, users commonly have 'hot streaks' of impact,
i.e., extended periods of high-impact tweets. Third, impact tends to
gradually build up before, and fall off after, a user's most impactful
tweet. We attempt to explain these characteristics using various
properties measured on social media, including the user's network,
content, activity, and experience, and find that changes in impact are
associated with significant changes in these properties. Our findings open
interesting avenues for future research on virality and influence on
social media.
Hot Streaks on Social Media
Kiran Garimella, Robert West
Source: arxiv.org (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D60c15bec1b-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=9e9ECWRiupinWlcHJt9hBKuZXQlKk2x3N2JxW-bAHfs&e=)
Editorial: Social networks analyses in primates, a multilevel perspective
https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D927cf19f3c-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=hv80PcMZ7Q0X_qFIDzscccgP-Q4NfIhz4A3rXrUf0s8&e=
Research using social network analyses has been booming since the start of
the 2000s, with studies not only in humans but also many nonhuman species.
Primates are no exception, with the number of retrievable items using the
keywords ˙˙social networks primates˙˙ increasing tenfold from 2000 to 2017
(Fig. 1a). Studies are in various domains including psychology, behavioral
sciences, and sociology, as well as neurosciences and infectious diseases
(Fig. 1b). To our knowledge, several special issues and books have focused
on animals (Croft et al. 2008; Whitehead 2008; Krause et al. 2009; Sheldon
2015; Sueur and Mery 2017) but with only one special issue devoted to
primates (Sueur et al. 2011). In the last decade studies have evolved from
describing structures (Manno 2008; Carter et al. 2013; Bret et al. 2013)
and topologies of social networks or centrality of group members according
to their sociodemographic characteristics (Lusseau and Newman 2004;
Kanngiesser et al. 2011), to a more holistic approach where the function
and evolution of networks are linked to ecological factors, behavioral
mechanisms, network topologies, and vice versa (Brent et al. 2013; Fisher
et al. 2016; Balasubramaniam et al. 2018). In this new special issue, our
aim is to present this integrative and multilevel approach along with
state-of-the-art methodologies and theoretical approaches for the study of
primate social networks.
Editorial: Social networks analyses in primates, a multilevel perspective
Ivan Puga-Gonzalez, Sebastian Sosa, Cédric Sueur
Primates
pp 1˙˙3
Source: link.springer.com (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D1d747eb4ca-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=F8uAtjIW-roDQzZKA8OnI8jgDCK9GxZHw5rsmu3Emks&e=)
Computational Methods for Identification and Modelling of Complex Biological Systems
Mathematical and computational models are key tools for understanding biological phenomena. In the last decades, scientific and technological advances have facilitated their evergrowing adoption in biologically oriented research. The strongly interdisciplinary character of these areas, in which biologists work along with researchers from physical sciences, engineering, and medicine, fosters the cross-fertilization between scientific fields. However, the large degree of structural and parametric uncertainty typically associated with biological processes makes it nontrivial to analyze them using techniques imported from fields in which these issues are less prevalent. Thus, there is a need for new methodological developments that fill this gap. The present special issue addresses this need by providing an overview of current open problems and presenting recent results regarding mathematical inference and modelling of biological systems.
Editorial Computational Methods for Identification and Modelling of
Complex Biological Systems Alejandro F. Villaverde, Carlo Cosentino,
Attila Gábor, and Gábor Szederkényi
Complexity
Volume 2019, Article ID 4951650, 3 pages
https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D9d5b9e1a48-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=c6NuwNoJvNI9Bt6wY5tlofTwPghpV8WFdoT0KRzWHQA&e=
Source: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.hindawi.com&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=ChdY92UhC35dpoAr51IA_lJLl0YdPeJJjXMj6d7pLM4&e= (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3Ddac2a4fb42-26e-3D55e25a0e3e&d=DwIFAw&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=5V38jfLgeT8PeCn5UiDgTRqAyl8Vg7LuCM1ieu88dnI&s=j_KDpGxHkEQd-PuP34t7yRQpHfpiG4jSUExpnB2PcmI&e=)
==============================================
Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.
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