scholarly journals The dynamics of information-driven coordination phenomena: A transfer entropy analysis

2016 ◽  
Vol 2 (4) ◽  
pp. e1501158 ◽  
Author(s):  
Javier Borge-Holthoefer ◽  
Nicola Perra ◽  
Bruno Gonçalves ◽  
Sandra González-Bailón ◽  
Alex Arenas ◽  
...  
Keyword(s):  
Information Transfer ◽  
Social Systems ◽  
Transfer Entropy ◽  
System Level ◽  
Directed Network ◽  
Characteristic Time Scale ◽  
Entropy Analysis ◽  
Collective Phenomena ◽  
Social Phenomena ◽  
Social Events

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

scholarly journals Calculating Transfer Entropy from Variance-Covariance Matrices Provides Insight into Allosteric Communication in ERK2

2020 ◽  
Author(s):  
Luisa Garcia Michel ◽  
Clara Keirns ◽  
Benjamin Ahlbrecht ◽  
Daniel Barr
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Experimental Studies ◽  
Mapk Signaling ◽  
Coupled Systems ◽  
Transfer Entropy ◽  
Entropy Analysis ◽  
Biomolecular Systems ◽  
Approximate Methods ◽  
Advantages And Disadvantages

<p>Transfer entropy methods provide an approach to understanding asymmetric information flow in coupled systems, with particular application to understanding allosteric interactions in biomolecular systems. Transfer entropy analysis holds the potential to reveal pathways or networks of residues that are coupled in their information flow and thus give new insights into folding and binding dynamics. Most current methods for calculating transfer entropy require very long simulations and almost equally long calculations of joint probability histograms to compute the information transfer that make these methods either functionally intractable or statistically unreliable. Available approximate methods based on graph and network theory approaches are rapid but lose sensitivity to the chemical nature of the biomolecules and thus are not applicable in mutation studies. We show that reliable estimates of the transfer entropy can be obtained from the variance-covariance matrix of atomic fluctuations, which converges quickly and retains sensitivity to the full chemical profile of the biomolecular system. We validate our method on ERK2, a well-studied kinase involved in the MAPK signaling cascade for which considerable computational, experimental, and mutation data are available. We present the results of transfer entropy analysis on data obtained from molecular dynamics simulations of wild type active and inactive ERK2, along with mutants Q103A, I84A, L73P, and G83A. We show that our method is consistent with the results of computational and experimental studies on ERK2, and we provide a method for interpreting networks of interconnected residues in the protein from a perspective of allosteric coupling. We introduce new insights about possible allosteric activity of the extreme N-terminal region of the kinase, which to date has been under-explored in the literature and may provide an important new direction for kinase studies. We also describe evidence that suggests activation may occur by different paths or routes in different mutants. Our results highlight systematic advantages and disadvantages of each method for calculating transfer entropy and show the important role of transfer entropy analysis for understanding allosteric behavior in biomolecular systems.</p>

scholarly journals Calculating Transfer Entropy from Variance-Covariance Matrices Provides Insight into Allosteric Communication in ERK2

2020 ◽  
Author(s):  
Luisa Garcia Michel ◽  
Clara Keirns ◽  
Benjamin Ahlbrecht ◽  
Daniel Barr
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Experimental Studies ◽  
Mapk Signaling ◽  
Coupled Systems ◽  
Transfer Entropy ◽  
Entropy Analysis ◽  
Biomolecular Systems ◽  
Approximate Methods ◽  
Advantages And Disadvantages

<p>Transfer entropy methods provide an approach to understanding asymmetric information flow in coupled systems, with particular application to understanding allosteric interactions in biomolecular systems. Transfer entropy analysis holds the potential to reveal pathways or networks of residues that are coupled in their information flow and thus give new insights into folding and binding dynamics. Most current methods for calculating transfer entropy require very long simulations and almost equally long calculations of joint probability histograms to compute the information transfer that make these methods either functionally intractable or statistically unreliable. Available approximate methods based on graph and network theory approaches are rapid but lose sensitivity to the chemical nature of the biomolecules and thus are not applicable in mutation studies. We show that reliable estimates of the transfer entropy can be obtained from the variance-covariance matrix of atomic fluctuations, which converges quickly and retains sensitivity to the full chemical profile of the biomolecular system. We validate our method on ERK2, a well-studied kinase involved in the MAPK signaling cascade for which considerable computational, experimental, and mutation data are available. We present the results of transfer entropy analysis on data obtained from molecular dynamics simulations of wild type active and inactive ERK2, along with mutants Q103A, I84A, L73P, and G83A. We show that our method is consistent with the results of computational and experimental studies on ERK2, and we provide a method for interpreting networks of interconnected residues in the protein from a perspective of allosteric coupling. We introduce new insights about possible allosteric activity of the extreme N-terminal region of the kinase, which to date has been under-explored in the literature and may provide an important new direction for kinase studies. We also describe evidence that suggests activation may occur by different paths or routes in different mutants. Our results highlight systematic advantages and disadvantages of each method for calculating transfer entropy and show the important role of transfer entropy analysis for understanding allosteric behavior in biomolecular systems.</p>

The Role of Social Logistics for the National, Economic and Social Security

2021 ◽  
Vol 39 (39) ◽  
pp. 54-69
Author(s):  
Vanya Banabakova
Keyword(s):  
Comparative Analysis ◽  
Social Security ◽  
National Security ◽  
Critical Analysis ◽  
System Approach ◽  
Human Factor ◽  
Social Systems ◽  
Social Phenomena ◽  
National Economic

Logistics continuously expands its application areas. In modern conditions, there is a need to apply logistics in areas not related to its traditional applications such as military and business spheres, resulting in the identification of a third area with the name social logistics. Social logistics aims to introduce a social (human) factor into the systems and to apply logistic principles and methods in solving the problems of society. Social logistics can be defined as a set of actions that ensure the effective functioning of social systems (such as a set of social phenomena, processes and subjects), applying the principles of logistics. For the purposes of this paper, a number of scientific approaches and methods have been applied, such as system approach, comparative analysis, critical analysis, synthesis and others. Social logistics plays an important role in national security, including economic and social security. The purpose of this paper is to explore the role of social logistics in enhancing national security, including economic and social security.

Community Differentiation and the Fallacy of Intenectorial Causation

1973 ◽  
Vol 32 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Berkley Spencer
Keyword(s):  
Social Systems ◽  
System Level ◽  
Independent System ◽  
Independent Variables ◽  
Underlying Dimension

The idea that independent variables "causing" modernization are to be found in the various societal sectors commonly distinguished by our cultural vernacular, for example, educational, economic, religious, industrial, etc., is challenged by data collected in 70 communities of highland Guatemala. The data suggest that such sectorial causal hypotheses are supported only because they reflect a common underlying dimension of social systems, differentiation, which cross-cuts a variety of institutional sectors. Alternatively, it is suggested that causation must be sought in other independent, system-level variables which likewise cross-cut a variety of institutional sectors.

scholarly journals Situational Breakdowns Beyond Protest Violence

2019 ◽  
pp. 129-168
Author(s):  
Anne Nassauer
Keyword(s):  
United States ◽  
African American ◽  
The United States ◽  
Crucial Importance ◽  
Social Phenomena ◽  
Systemic Racism ◽  
Context Factors ◽  
Social Events ◽  
Micro Level

Chapter 9 explores whether the books’ findings hold in other contexts by examining other instances of surprising outcomes. First, the chapter discusses the outbreak of violence in uprisings after police shootings of African American citizens in the United States, such as Ferguson, Missouri, in 2014 and Baltimore, Maryland, in 2015. The first section takes a detailed look at the role of background and context factors (such as symbolic and systemic racism) and situational patterns in uprisings turning violent. Then the chapter discusses successful and failed armed store robberies. Here the surprising outcome is not violence but armed criminals failing to get the money from an unarmed store clerk. Findings suggest similar patterns of situational breakdowns in these occurrences as in protests and uprisings. Overall, the chapter discusses the crucial importance of the micro-level of social phenomena: if routines of both collective and individual social events are disrupted, surprising outcomes occur.

scholarly journals Directed networks as a novel way to describe and analyze cardiac excitation: Directed Graph mapping

2019 ◽  
Author(s):  
Nele Vandersickel ◽  
Enid Van Nieuwenhuyse ◽  
Nico Van Cleemput ◽  
Jan Goedgebeur ◽  
Milad El Haddad ◽  
...  
Keyword(s):  
Cardiac Arrhythmias ◽  
Normal Sinus Rhythm ◽  
Social Systems ◽  
Daily Practice ◽  
Directed Network ◽  
Directed Networks ◽  
Normal Sinus ◽  
Graph Mapping ◽  
Brain Data ◽  
Cardiac Excitation

AbstractNetworks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proofof-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow to determine the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood.

GWAP as a Tool to Analyze, Design, and Test Geo-Social Systems

2013 ◽  
pp. 380-407 ◽  
Author(s):  
Martina Deplano ◽  
Giancarlo Ruffo
Keyword(s):  
Social Media ◽  
Information Systems ◽  
Real Time ◽  
Mobile Devices ◽  
General Framework ◽  
Social Dynamics ◽  
Social Systems ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Social Events

In this chapter, the authors discuss the state-of-the-art of Geo-Social systems and Recommender systems, which are becoming extremely popular for users accessing social media trough mobile devices. Moreover, they introduce a general framework based on the interaction among those systems and the “Game With A Purpose” (GWAP) paradigm. The proposed framework/platform can help researchers to understand geo-social dynamics in order to design and test new services, such as recommenders of places of interest for tourists, real-time traffic information systems, personalized suggestions of social events, and so forth. To target the governance of such complexity, relevant data must be collected by the investigators, shared with the community, and analyzed to find dynamical patterns that correlate spatial-temporal information with the user’s preferences and objectives. The authors argue that the GWAP approach can be exploited to successfully satisfy many of these tasks.

scholarly journals Novel Node Centrality-Based Efficient Empirical Robustness Assessment for Directed Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xiaolong Deng ◽  
Hao Ding ◽  
Yong Chen ◽  
Cai Chen ◽  
Tiejun Lv
Keyword(s):  
Social Network ◽  
Vulnerability Assessment ◽  
Online Social Networks ◽  
Information Transfer ◽  
Large Scale ◽  
Real Life ◽  
Clustering Coefficient ◽  
Network Robustness ◽  
Directed Network ◽  
Online Social Media

In recent years, while extensive researches on various networks properties have been proposed and accomplished, little has been proposed and done on network robustness and node vulnerability assessment under cascades in directed large-scale online community networks. In essential, an online directed social network is a group-centered and information spread-dominated online platform which is very different from the traditional undirected social network. Some further research studies have indicated that the online social network has high robustness to random removals of nodes but fails to the intentional attacks, particularly to those attacks based on node betweenness or node directed coefficient. To explore on the robustness of directed social network, in this article, we have proposed two novel node centralities of ITG (information transfer gain-based probability clustering coefficient) and I M p v (directed path-based node importance centrality). These two new centrality models are designed to capture this cascading effect in directed online social networks. Furthermore, we also propose a new and highly efficient computing method based on iterations for I M p v . Then, with the abundant experiments on the synthetic signed network and real-life networks derived from directed online social media and directed human mobile phone calling network, it has been proved that our ITG and I M p v based on directed social network robustness and node vulnerability assessment method is more accurate, efficient, and faster than several traditional centrality methods such as degree and betweenness. And we also have proposed the solid reasoning and proof process of iteration times k in computation of I M p v . To the best knowledge of us, our research has drawn some new light on the leading edge of robustness on the directed social network.

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