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

Have a nice post-Hanukkah 😊


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

Getting It Done; Getting It Out: A Practical Guide to Writing, Publishing, Presenting, and Promoting in the Social Sciences—
                coming in 2021 (Guilford Press)
Networked: The New Social Operating System  Lee Rainie & Barry Wellman (MIT Press)  https://urldefense.proofpoint.com/v2/url?u=http-3A__amzn.to_zXZg39&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=iQIo202b_xDZYcIa37QGakplgdXTqM0wT_epx7BdEAU&e= 
Oxford Interview with Cody Kommers on the Start of the Network Revolution (2020, https://urldefense.proofpoint.com/v2/url?u=https-3A__www.codykommers.com_post_38-2Dbarry-2Dwellman-2Don-2Dthe-2Dacademic-2Dsocial-2Dnetwork&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=ZURrT0Vuu1kcK7orD2n3nwzAv-OepLDLbpVREcR3ZJs&e= 

           Kyle Lowry is my spirit animal!
    Bit by bit, putting it together!--Sondheim
It's Always Something!--Roseanne Roseannadanna


-----Original Message-----
From: Complexity Digest <[log in to unmask]> 
Sent: Monday, December 21, 2020 7:04 AM
To: Barry <[log in to unmask]>
Subject: 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-3D02b1851e87-26e-3D55e25a0e3e&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=aRG9Imrk5S7rls10kQ-BMuOSbyB0pV5IVqNqijBjd18&e= 


Eight years of homicide evolution in Monterrey, Mexico: a network approach

   Rodrigo Dorantes-Gilardi, Diana García-Cortés, Hiram Hernández-Ramos & Jesús Espinal-Enríquez
Scientific Reports volume 10, Article number: 21564 (2020)

Homicide is without doubt one of Mexico’s most important security problems, with data showing that this dismal kind of violence sky-rocketed shortly after the war on drugs was declared in 2007. Since then, violent war-like zones have appeared and disappeared throughout Mexico, causing unfathomable human, social and economic losses. One of the most emblematic of these zones is the Monterrey metropolitan area (MMA), a central scenario in the narco-war. Being an important metropolitan area in Mexico and a business hub, MMA has counted hundreds to thousands of casualties. In spite of several approaches being developed to understand and analyze crime in general, and homicide in particular, the lack of accurate spatio-temporal homicide data results in incomplete descriptions. In order to describe the manner in which violence has evolved and spread in time and space through the city, here we propose a network-based approach. For this purpose, we define a homicide network where nodes are
geographical entities that are connected through spatial and temporal relationships. We analyzed the time series of homicides in different municipalities and neighborhoods of the MMA, to observe whether or not a global correlation appeared. We studied the spatial correlation between neighborhoods where homicides took place, to observe whether distance is a factor of influence in the frequency of homicides. We constructed yearly co-occurrence networks, by correlating neighborhoods with homicides happening within a same week, and counting the co-occurrences of these neighborhood pairs in 1 year. We also constructed a crime network by aggregating all data of homicides, eliminating the temporal correlation, in order to observe whether homicide clusters appeared, and what those clusters were distributed geographically. Finally, we correlated the location and frequency of homicides with roads, freeways and highways, to observe if a trend in the homicidal violence appeared. Our network approach in
the homicide evolution of MMA allows us to identify that (1) analyzing the whole 86-month period, we observed a correlation between close cities, which decreases in distant places. (2) at neighborhood level, correlations are not distance-dependent, on the contrary, highest co-occurrences appeared between distant neighborhoods and a polygon formed by close neighborhoods in downtown Monterrey. Moreover, (3) An elevated number of homicides occur close to the 85th freeway, which connects MMA with the US border. (4) Some socioeconomic barriers determine the presence of homicide violence. Finally, (5) we show a relation between homicidal crime and the urban landscape by studying the distance of safe and violent neighborhoods to the closest highway and by studying the evolution of highway and crime distance over the cartel-related years and the following period. With this approach, we are able to describe the spatial and temporal evolution of homicidal crime in a metropolitan area.

Read the full article at: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.nature.com&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=sAis2ndAV8P5rx8Ac6A3wGCRb2aEihuF5R1TiJ_YUfM&e=  (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3De550bc7822-26e-3D55e25a0e3e&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=JxJqtsdo4CIleOLSuAxqcXb9jvEyFrdNlDgBuc4BOVA&e= )



Arithmetic success and gender-based characterization of brain connectivity across EEG bands

   Sait Demir, İlker Türker

Biomedical Signal Processing and Control
Volume 64, February 2021, 102222

• Functional brain networks employing coherence method is conducted in a comparative manner across EEG bands.

• Female brain is more connected under rest condition, while male brain boosts connectivity under arithmetic workload.

• Unsuccessful brains yield more assortative behavior based on beta band networks.

• Arithmetically successful brains yield greater connectivity under rest condition for most EEG bands.

• Theta band better diagnoses gender-based differences, while gamma band better discriminates success-based connectivity.

Read the full article at: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.sciencedirect.com&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=2VVo_y057GtSBd6GnP8A8n0rnfvn-9VGzSySX1u3Dfo&e=  (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3Db1e4ddf039-26e-3D55e25a0e3e&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=aestmBdxHGup9_cZ5VMhBF1-iU36nipR4_XPSGYpQQE&e= )

Edge-based analysis of networks: curvatures of graphs and hypergraphs

   Marzieh Eidi, Amirhossein Farzam, Wilmer Leal, Areejit Samal & Jürgen Jost
Theory in Biosciences volume 139, pages337–348(2020)

The relations, rather than the elements, constitute the structure of networks. We therefore develop a systematic approach to the analysis of networks, modelled as graphs or hypergraphs, that is based on structural properties of (hyper)edges, instead of vertices. For that purpose, we utilize so-called network curvatures. These curvatures quantify the local structural properties of (hyper)edges, that is, how, and how well, they are connected to others. In the case of directed networks, they assess the input they receive and the output they produce, and relations between them. With those tools, we can investigate biological networks. As examples, we apply our methods here to protein–protein interaction, transcriptional regulatory and metabolic networks.

Read the full article at: link.springer.com (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D7597639fd0-26e-3D55e25a0e3e&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=rsUhyx-wQI4ghz4g1ds4Ma5Ns21rj8raB2LDD9en-IQ&e= )




The Emergence of Higher-Order Structure in Scientific and Technological Knowledge Networks

   Thomas Gebhart, Russell J. Funk

The growth of science and technology is a recombinative process, wherein new discoveries and inventions are built from prior knowledge. Yet relatively little is known about the manner in which scientific and technological knowledge develop and coalesce into larger structures that enable or constrain future breakthroughs. Network science has recently emerged as a framework for measuring the structure and dynamics of knowledge. While helpful, existing approaches struggle to capture the global properties of the underlying networks, leading to conflicting observations about the nature of scientific and technological progress. We bridge this methodological gap using tools from algebraic topology to characterize the higher-order structure of knowledge networks in science and technology across scale. We observe rapid growth in the higher-order structure of knowledge in many scientific and technological fields. This growth is not observable using traditional network measures. We further demonstrate
that the emergence of higher-order structure coincides with decline in lower-order structure, and has historically far outpaced the corresponding emergence of higher-order structure in scientific and technological collaboration networks. Up to a point, increases in higher-order structure are associated with better outcomes, as measured by the novelty and impact of papers and patents. However, the nature of science and technology produced under higher-order regimes also appears to be qualitatively different from that produced under lower-order ones, with the former exhibiting greater linguistic abstractness and greater tendencies for building upon prior streams of knowledge.

Read the full article at: arxiv.org (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D1b0d75cfe1-26e-3D55e25a0e3e&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=-mSfdcEz6f8wBuZ39RVpWJJFHHX_26mVw61lAamqGag&e= )



What’s next for remote work: An analysis of 2,000 tasks, 800 jobs, and nine countries

   Hybrid models of remote work are likely to persist in the wake of the pandemic, mostly for a highly educated, well-paid minority of the workforce.

Read the full article at: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mckinsey.com&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=sMb45FnR0lxvVRvMws89l66IJNaxCMWKLbm7UXiqwxU&e=  (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D0e4111d1da-26e-3D55e25a0e3e&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=SMffQMGSa2ivMdcJXAOxetFxAugd0pgn3cC1IwM5ZXw&s=WgJbPj4XAQn-B_0HicPyX1qjmn399hgkcDINZ-x5ULM&e= )



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