networks and network weaving
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Collecting and comparing design principles | Solving for Pattern

Collecting and comparing design principles | Solving for Pattern | networks and network weaving | Scoop.it
The best design principles are intriguing, informative, and also revealing about the perceived design context.
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networks and network weaving
How networks can transform our world
Curated by june holley
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How Twitter Users Can Generate Better Ideas

There’s a link between the amount of diversity in employees’ Twitter networks and the quality of their ideas.
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The Open Organization Workbook: Download the PDF

The Open Organization Workbook: Download the PDF | networks and network weaving | Scoop.it
Download the fifth companion volume in The Open Organization book series on how to build a culture of innovation
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Gallery: How networks help us understand the world |

Gallery: How networks help us understand the world | | networks and network weaving | Scoop.it
Data visualization expert Manuel Lima shares some of his favorite graphics showing how the network is a powerful way to reflect the world.
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‘Weaving’ — 21st Century Servant Leadership for Systemic Health

‘Weaving’ — 21st Century Servant Leadership for Systemic Health | networks and network weaving | Scoop.it
WE LIVE in a fractured world of growing complexity, facing convergent crises the potential impact of which baffles comprehension. One can’t but recoil from the possible dystopias that now seem so…
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Are Backbone Organizations Eroding the Norms that Make Networks Succeed?

Are Backbone Organizations Eroding the Norms that Make Networks Succeed? | networks and network weaving | Scoop.it
This article challenges a core collective impact model tenet—that networks must be supported by a backbone organization. One danger of backbones is they can inadvertently defuse the grassroots energy that is so central to effective social change.
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Network Weaving 101 (PDF Download Available)

Network Weaving 101 (PDF Download Available) | networks and network weaving | Scoop.it
Full-text (PDF) | Network Weaving 101 | ResearchGate, the professional network for scientists.
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Network Weaving {Phase II: EPIK Alliance Meeting Report} | EPIK – Deliberate Digital

Network Weaving {Phase II: EPIK Alliance Meeting Report} | EPIK – Deliberate Digital | networks and network weaving | Scoop.it
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Building a network for People Powered Change

Building a network for People Powered Change | networks and network weaving | Scoop.it

Update from March 2012 on work with the Big Lottery Fund to help them become a more networked organisation, and extend their support for community groups 


Via David Wilcox, Drew Mackie
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Detecting reciprocity at a global scale

Reciprocity stabilizes cooperation from the level of microbes all the way up to humans interacting in small groups, but does reciprocity also underlie stable cooperation between larger human agglomerations, such as nation states? Famously, evolutionary models show that reciprocity could emerge as a widespread strategy for achieving international cooperation. However, existing studies have only detected reciprocity-driven cooperation in a small number of country pairs. We apply a new method for detecting mutual influence in dynamical systems to a new large-scale data set that records state interactions with high temporal resolution. Doing so, we detect reciprocity between many country pairs in the international system and find that these reciprocating country pairs exhibit qualitatively different cooperative dynamics when compared to nonreciprocating pairs. Consistent with evolutionary theories of cooperation, reciprocating country pairs exhibit higher levels of stable cooperation and are more likely to punish instances of noncooperation. However, countries in reciprocity-based relationships are also quicker to forgive single acts of noncooperation by eventually returning to previous levels of mutual cooperation. By contrast, nonreciprocating pairs are more likely to exploit each other’s cooperation via higher rates of defection. Together, these findings provide the strongest evidence to date that reciprocity is a widespread mechanism for achieving international cooperation.

 

Detecting reciprocity at a global scale
Morgan R. Frank, Nick Obradovich, Lijun Sun, Wei Lee Woon, Brad L. LeVeck and Iyad Rahwan,
Science Advances  03 Jan 2018:
Vol. 4, no. 1, eaao5348
DOI: 10.1126/sciadv.aao5348


Via Complexity Digest
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The role of gender in social network organization

The role of gender in social network organization | networks and network weaving | Scoop.it
The digital traces we leave behind when engaging with the modern world offer an interesting lens through which we study behavioral patterns as expression of gender. Although gender differentiation has been observed in a number of settings, the majority of studies focus on a single data stream in isolation. Here we use a dataset of high resolution data collected using mobile phones, as well as detailed questionnaires, to study gender differences in a large cohort. We consider mobility behavior and individual personality traits among a group of more than 800 university students. We also investigate interactions among them expressed via person-to-person contacts, interactions on online social networks, and telecommunication. Thus, we are able to study the differences between male and female behavior captured through a multitude of channels for a single cohort. We find that while the two genders are similar in a number of aspects, there are robust deviations that include multiple facets of social interactions, suggesting the existence of inherent behavioral differences. Finally, we quantify how aspects of an individual’s characteristics and social behavior reveals their gender by posing it as a classification problem. We ask: How well can we distinguish between male and female study participants based on behavior alone? Which behavioral features are most predictive?
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Community and belonging in networks for change

Community and belonging in networks for change | networks and network weaving | Scoop.it
Ever wondered why some things always get a good turnout and others don’t, even if they’re both excellent and worthwhile? Our peer network programme coordinator Megan, suggests that pee
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Scant Evidence of Power Laws Found in Real-World Networks

Scant Evidence of Power Laws Found in Real-World Networks | networks and network weaving | Scoop.it
A new study challenges one of the most celebrated and controversial ideas in network science.
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Why choose transformative over sustaining innovation?

How do we keep the lights on, avoid revolution and turmoil, keep children in school and people in work, yet still manage to fundamentally transform the human presence on planet Earth before ‘business as usual’ leads to run-away climate change, a drastically impoverished biosphere, and the early demise of our species?
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How to Create a 'Live Link' from sumApp to Kumu for Real Time Network Mapping

Follow-up to Maya Townsend interview about real-time network mapping using sumApp and Kumu
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Dynamic patterns of information flow in complex networks

Dynamic patterns of information flow in complex networks | networks and network weaving | Scoop.it

Although networks are extensively used to visualize information flow in biological, social and technological systems, translating topology into dynamic flow continues to challenge us, as similar networks exhibit fundamentally different flow patterns, driven by different interaction mechanisms. To uncover a network’s actual flow patterns, here we use a perturbative formalism, analytically tracking the contribution of all nodes/paths to the flow of information, exposing the rules that link structure and dynamic information flow for a broad range of nonlinear systems. We find that the diversity of flow patterns can be mapped into a single universal function, characterizing the interplay between the system’s topology and its dynamics, ultimately allowing us to identify the network’s main arteries of information flow. Counter-intuitively, our formalism predicts a family of frequently encountered dynamics where the flow of information avoids the hubs, favoring the network’s peripheral pathways, a striking disparity between structure and dynamics.

 

Dynamic patterns of information flow in complex networks
Uzi Harush & Baruch Barzel
Nature Communicationsvolume 8, Article number: 2181 (2017)
doi:10.1038/s41467-017-01916-3


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Empowering Stakeholders to Become Network Weavers

In this presentation, lean about value of the network weaver, how to foster and support your own network weavers online, a four-part support system for doing s…
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What Does the Collaboration “Field” Look Like? | Groupaya

What Does the Collaboration “Field” Look Like? | Groupaya | networks and network weaving | Scoop.it

I've chosen this piece becaue (a) collaboration is a topic very close to my heart as a KM professional and  (b) it provides actual data that confirms something I've long suspected - the gap between technologists and organisational change skills.

 

To quote from the author:

I was disappointed, but not surprised, that “collaboration” as a skill was mostly lumped with technology skills. Folks in the Enterprise 2.0 space, for example, have almost no overlap with organizational development professionals. It’s a troubling trend. Although people are fond of saying, “It’s not about technology, it’s about people,” there’s not much practice validating that mantra.

 

Value: 9/10


Via Stephen Dale, David Wilcox, Drew Mackie
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The most important connection in any network is the local – Deborah M Gordon | Aeon Essays

The most important connection in any network is the local – Deborah M Gordon | Aeon Essays | networks and network weaving | Scoop.it
Networks regulate everything from ant colonies and middle schools to epidemics and the internet. Here’s how they work
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Intermediate Levels of Network Heterogeneity Provide the Best Evolutionary Outcomes

Intermediate Levels of Network Heterogeneity Provide the Best Evolutionary Outcomes | networks and network weaving | Scoop.it
Complex networks impact the diffusion of ideas and innovations, the formation of opinions, and the evolution of cooperative behavior. In this context, heterogeneous structures have been shown to generate a coordination-like dynamics that drives a population towards a monomorphic state. In contrast, homogeneous networks tend to result in a stable co-existence of multiple traits in…
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MAYA TOWNSEND CONNECTS THE DOTS WITH REALTIME NETWORK MAPPING | Greater Than The Sum

MAYA TOWNSEND CONNECTS THE DOTS WITH REALTIME NETWORK MAPPING | Greater Than The Sum | networks and network weaving | Scoop.it
One of the important pieces is to get that sense of ‘we’re not in this alone,’ that ‘we have more connections than we know.’
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Thinking Fast and Slow on Networks: Co-evolution of Cognition and Cooperation in Structured Populations by Mohsen Mosleh, David G. Rand :: SSRN

Thinking Fast and Slow on Networks: Co-evolution of Cognition and Cooperation in Structured Populations by Mohsen Mosleh, David G. Rand :: SSRN | networks and network weaving | Scoop.it
Spatial structure is one of the most studied mechanisms in evolutionary game theory. Here, we explore the consequences of spatial structure for a question which
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Scale-free networks are rare

A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree k follows a power law, decaying like k^−α, often with 2<α<3. However, empirical evidence for this belief derives from a relatively small number of real-world networks. We test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources. We fit the power-law model to each degree distribution, test its statistical plausibility, and compare it via a likelihood ratio test to alternative, non-scale-free models, e.g., the log-normal. Across domains, we find that scale-free networks are rare, with only 4% exhibiting the strongest-possible evidence of scale-free structure and 52% exhibiting the weakest-possible evidence. Furthermore, evidence of scale-free structure is not uniformly distributed across sources: social networks are at best weakly scale free, while a handful of technological and biological networks can be called strongly scale free. These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain.

 

Scale-free networks are rare
Anna D. Broido, Aaron Clauset


Via Complexity Digest
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Complexity Digest's curator insight, January 26, 12:04 PM

See Also:

Twitter discussion, including Aaron Clauset, Laszlo Barabasi, Alex Vespignani, Duncan Watts, Stefano Zapperi, Petter Holme, Gabor Vattay, et al.

https://twitter.com/manlius84/timelines/952248309720211458 

Blog post by Petter Holme

https://petterhol.me/2018/01/12/me-and-power-laws/