The document discusses the need for a democratic, scalable, and sustainable digital future. It suggests that digital diversity is possible but fragile. Research shows that routing performance can be improved by using multiple networks simultaneously if they exhibit geometric correlations between node coordinates. Incentives like "Social Bitcoin" could sustain a diverse, decentralized digital world by rewarding users for routing information. The goal is for self-organization of the digital world to create a desirable future with robust digital diversity and efficient search/navigation.
Is bigger always better? How local online social networks can outperform glob...Kolja Kleineberg
The overwhelming success of online social networks, the key actors in the cosmos of the Web
2.0, has reshaped human interactions on a worldwide scale. To help understand the fundamental
mechanisms which determine the fate of online social networks at the system level, we describe the
digital world as a complex ecosystem of interacting networks. In this paper, we discuss the impact
of heterogeneity in network fitnesses induced by competition between an international network,
such as Facebook, and local services.To this end, we construct a 1:1000 scale model of the digital
world, consisting of the 80 countries with the most Internet users. We show how inter-country social
ties induce increased fitness of the international network. Under certain conditions, this leads to
the extinction of local networks; whereas under different conditions, local networks can persist and
even dominate the international network completely. These findings provide new insights into the
possibilities for preserving digital diversity.
(Digital) networks and the science of complex systemsKolja Kleineberg
The document discusses complex systems and networks, focusing on digital networks. It describes how network models can help understand complex systems like the internet and financial networks. Digital networks have significant power to influence behaviors and spread information. While this power in a single network could be problematic, models show how diversity across multiple competing networks can allow for coexistence, though this is fragile. Sustaining diversity requires balancing viral and mass media influences.
Structure and dynamics of multiplex networks: beyond degree correlationsKolja Kleineberg
The organization of constituent network layers to multiplex networks has recently attracted a lot of attention. Here, we show empirical evidence for the existence of relations between the layers of real multiplex networks that go beyond degree correlations. These relations consist of correlations in hidden metric spaces that underlie the observed topology. We discuss the impact and applications of these relations for trans-layer link prediction, community detection, navigation, game theory, and especially for the robustness of multiplex networks against random failures and targeted attacks. We show that these relations lead to fundamentally new behaviors, which emphasizes the importance to consider organizational principles of multiplex networks beyond degree correlations in future research.
Ecology 2.0: Coexistence and domination among interacting networksKolja Kleineberg
The overwhelming success of the web 2.0, with online social networks as key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of these services for the first time has allowed researchers to quantify large-scale social patterns. However, the mechanisms that determine the fate of networks at a system level are still poorly understood. For instance, the simultaneous existence of numerous digital services naturally raises the question under which conditions these services can coexist. In analogy to population dynamics, the digital world is forming a complex ecosystem of interacting networks whose fitnesses depend on their ability to attract and maintain users' attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits a stable coexistence of several networks as well as the domination of a single one, in contrast to the principle of competitive exclusion. Interestingly, our model also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.
Hidden geometric correlations in real multiplex networksKolja Kleineberg
Read the paper at http://www.nature.com/nphys/journal/vaop/ncurrent/full/nphys3812.html
Real networks often form interacting parts of larger and more complex systems. Examples can be found in different domains, ranging from the Internet to structural and functional brain networks. Here, we show that these multiplex systems are not random combinations of single network layers. Instead, they are organized in specific ways dictated by hidden geometric correlations between the layers. We find that these correlations are significant in different real multiplexes, and form a key framework for answering many important questions. Specifically, we show that these geometric correlations facilitate the definition and detection of multidimensional communities, which are sets of nodes that are simultaneously similar in multiple layers. They also enable accurate trans-layer link prediction, meaning that connections in one layer can be predicted by observing the hidden geometric space of another layer. And they allow efficient targeted navigation in the multilayer system using only local knowledge, outperforming navigation in the single layers only if the geometric correlations are sufficiently strong.
Collective navigation of complex networks: Participatory greedy routingKolja Kleineberg
Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However, in reality most agents will deny to forward messages, which has a cost, and navigation is impossible. Can we design appropriate incentives that lead to participation and global navigability? Here, we present an evolutionary game where agents share the value generated by successful delivery of information or goods. We show that global navigability can emerge, but its complete breakdown is possible as well. Furthermore, we show that the system tends to self-organize into local clusters of agents who participate in the navigation. This organizational principle can be exploited to favor the emergence of global navigability in the system.
Geometric correlations in multiplexes and how they make them more robustKolja Kleineberg
This document discusses research on the structure and dynamics of multiplex networks. It begins by introducing the concept of multiplex networks, which have the same nodes existing across different network layers. It then discusses how degree correlations and geometric correlations between the positions of nodes in the hidden metric spaces underlying different network layers have been found in real multiplex systems. The document explores how these geometric correlations allow for applications like better identifying communities of nodes, improved link prediction between layers, and more efficient navigation across the network layers.
The Hidden Geometry of Multiplex Networks @ Next Generation Network Analytics Kolja Kleineberg
The document summarizes research on the hidden geometry of multiplex networks. It finds that real-world multiplex networks often have correlated geometric properties between network layers, with nodes maintaining similar radial and angular coordinates. This has implications like communities of nodes being similar across layers and hyperbolic distance in one layer predicting connections in another. A geometric multiplex model is introduced to generate realistic multiplex networks with tunable geometric correlations between layers.
Is bigger always better? How local online social networks can outperform glob...Kolja Kleineberg
The overwhelming success of online social networks, the key actors in the cosmos of the Web
2.0, has reshaped human interactions on a worldwide scale. To help understand the fundamental
mechanisms which determine the fate of online social networks at the system level, we describe the
digital world as a complex ecosystem of interacting networks. In this paper, we discuss the impact
of heterogeneity in network fitnesses induced by competition between an international network,
such as Facebook, and local services.To this end, we construct a 1:1000 scale model of the digital
world, consisting of the 80 countries with the most Internet users. We show how inter-country social
ties induce increased fitness of the international network. Under certain conditions, this leads to
the extinction of local networks; whereas under different conditions, local networks can persist and
even dominate the international network completely. These findings provide new insights into the
possibilities for preserving digital diversity.
(Digital) networks and the science of complex systemsKolja Kleineberg
The document discusses complex systems and networks, focusing on digital networks. It describes how network models can help understand complex systems like the internet and financial networks. Digital networks have significant power to influence behaviors and spread information. While this power in a single network could be problematic, models show how diversity across multiple competing networks can allow for coexistence, though this is fragile. Sustaining diversity requires balancing viral and mass media influences.
Structure and dynamics of multiplex networks: beyond degree correlationsKolja Kleineberg
The organization of constituent network layers to multiplex networks has recently attracted a lot of attention. Here, we show empirical evidence for the existence of relations between the layers of real multiplex networks that go beyond degree correlations. These relations consist of correlations in hidden metric spaces that underlie the observed topology. We discuss the impact and applications of these relations for trans-layer link prediction, community detection, navigation, game theory, and especially for the robustness of multiplex networks against random failures and targeted attacks. We show that these relations lead to fundamentally new behaviors, which emphasizes the importance to consider organizational principles of multiplex networks beyond degree correlations in future research.
Ecology 2.0: Coexistence and domination among interacting networksKolja Kleineberg
The overwhelming success of the web 2.0, with online social networks as key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of these services for the first time has allowed researchers to quantify large-scale social patterns. However, the mechanisms that determine the fate of networks at a system level are still poorly understood. For instance, the simultaneous existence of numerous digital services naturally raises the question under which conditions these services can coexist. In analogy to population dynamics, the digital world is forming a complex ecosystem of interacting networks whose fitnesses depend on their ability to attract and maintain users' attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits a stable coexistence of several networks as well as the domination of a single one, in contrast to the principle of competitive exclusion. Interestingly, our model also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.
Hidden geometric correlations in real multiplex networksKolja Kleineberg
Read the paper at http://www.nature.com/nphys/journal/vaop/ncurrent/full/nphys3812.html
Real networks often form interacting parts of larger and more complex systems. Examples can be found in different domains, ranging from the Internet to structural and functional brain networks. Here, we show that these multiplex systems are not random combinations of single network layers. Instead, they are organized in specific ways dictated by hidden geometric correlations between the layers. We find that these correlations are significant in different real multiplexes, and form a key framework for answering many important questions. Specifically, we show that these geometric correlations facilitate the definition and detection of multidimensional communities, which are sets of nodes that are simultaneously similar in multiple layers. They also enable accurate trans-layer link prediction, meaning that connections in one layer can be predicted by observing the hidden geometric space of another layer. And they allow efficient targeted navigation in the multilayer system using only local knowledge, outperforming navigation in the single layers only if the geometric correlations are sufficiently strong.
Collective navigation of complex networks: Participatory greedy routingKolja Kleineberg
Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However, in reality most agents will deny to forward messages, which has a cost, and navigation is impossible. Can we design appropriate incentives that lead to participation and global navigability? Here, we present an evolutionary game where agents share the value generated by successful delivery of information or goods. We show that global navigability can emerge, but its complete breakdown is possible as well. Furthermore, we show that the system tends to self-organize into local clusters of agents who participate in the navigation. This organizational principle can be exploited to favor the emergence of global navigability in the system.
Geometric correlations in multiplexes and how they make them more robustKolja Kleineberg
This document discusses research on the structure and dynamics of multiplex networks. It begins by introducing the concept of multiplex networks, which have the same nodes existing across different network layers. It then discusses how degree correlations and geometric correlations between the positions of nodes in the hidden metric spaces underlying different network layers have been found in real multiplex systems. The document explores how these geometric correlations allow for applications like better identifying communities of nodes, improved link prediction between layers, and more efficient navigation across the network layers.
The Hidden Geometry of Multiplex Networks @ Next Generation Network Analytics Kolja Kleineberg
The document summarizes research on the hidden geometry of multiplex networks. It finds that real-world multiplex networks often have correlated geometric properties between network layers, with nodes maintaining similar radial and angular coordinates. This has implications like communities of nodes being similar across layers and hyperbolic distance in one layer predicting connections in another. A geometric multiplex model is introduced to generate realistic multiplex networks with tunable geometric correlations between layers.
Spatial patterns in evolutionary games on scale-free networks and multiplexesKolja Kleineberg
The document discusses evolutionary games on scale-free networks and multiplexes. It finds that cooperation can be sustained in metric clusters that form on scale-free networks. These metric clusters shield cooperators from surrounding defectors similar to spatial selection. The survival of metric clusters is favored when the network is less heterogeneous, has a higher clustering coefficient, and the clusters are larger. Similar clusters are also found for different games played on correlated multiplex networks.
Interplay between social influence and competitive strategical games in multi...Kolja Kleineberg
The document discusses the interplay between social influence and competitive strategic games on multiplex networks. It shows that an opinion dynamics model with pro-cooperation bias can transform a prisoner's dilemma game into a snowdrift game. Considering multiplex topology is important, as correlations between network layers can have an even bigger impact on cooperation than individual layer topologies alone. When similarity correlations are present between layers, cooperative clusters can form across both layers through self-organization.
Towards controlling evolutionary dynamics through network geometry: some very...Kolja Kleineberg
The document discusses how network geometry can control evolutionary dynamics through the formation of cooperating clusters. It presents examples showing how the placement of initial cooperators in metric space clusters versus randomly can influence whether cooperation emerges in evolutionary games and navigation processes on networks. The author suggests that network geometry may allow active control of evolutionary dynamics by strategically placing control agents based on the underlying geometry.
Geometric correlations mitigate the extreme vulnerability of multiplex networ...Kolja Kleineberg
The document discusses how geometric correlations between layers in multiplex networks can mitigate their vulnerability to targeted attacks. It finds that while degree correlations provide some robustness to random failures, they do not prevent catastrophic cascades under targeted attacks. However, geometric or similarity correlations, which place similar nodes close together in an underlying metric space representing each layer, can significantly increase robustness to targeted attacks. This effect is demonstrated through a model incorporating such correlations, as well as analyses of real-world multiplex networks that exhibit stronger geometric correlations.
A Proposed Algorithm to Detect the Largest Community Based On Depth LevelEswar Publications
The incredible rising of online networks show that these networks are complex and involving massive data.Giving a very strong interest to set of techniques developed for mining these networks. The clique problem is a well known NP-Hard problem in graph mining. One of the fundamental applications for it is the community detection. It helps to understand and model the network structure which has been a fundamental problem in several fields. In literature, the exponentially increasing computation time of this problem make the quality of these solutions is limited and infeasible for massive graphs. Furthermore, most of the proposed approaches are able to detect only disjoint communities. In this paper, we present a new clique based approach for fast and efficient overlapping
community detection. The work overcomes the short falls of clique percolation method (CPM), one of most popular and commonly used methods in this area. The shortfalls occur due to brute force algorithm for enumerating maximal cliques and also the missing out many vertices thatleads to poor node coverage. The proposed work overcome these shortfalls producing NMC method for enumerating maximal cliques then detects overlapping communities using three different community scales based on three different depth levels to assure high nodes coverage and detects the largest communities. The clustering coefficient and cluster density are used to measure the quality. The work also provide experimental results on benchmark real world network to
demonstrate the efficiency and compare the new proposed algorithm with CPM method, The proposed algorithm is able to quickly discover the maximal cliques and detects overlapping community with interesting remarks and findings.
This document summarizes two presentations about community detection in social media networks. The first presentation discusses using edge content, like image tags, to help identify communities in networks. The second focuses on leveraging interaction intensities on Twitter to detect communities that form around certain events over time. Both aim to improve on traditional methods that only consider network structure.
This document discusses community detection in social media and online networks. It defines communities as groups of densely interconnected nodes in a graph. It outlines various algorithms for detecting communities, including graph partitioning, k-clique detection, core decomposition, divisive algorithms based on edge centrality, and modularity maximization approaches. It also discusses local community detection methods and evaluation of community detection results.
MODELING SOCIAL GAUSS-MARKOV MOBILITY FOR OPPORTUNISTIC NETWORK csandit
Mobility is attracting more and more interests due to its importance for data forwarding
mechanisms in many networks such as mobile opportunistic network. In everyday life mobile
nodes are often carried by human. Thus, mobile nodes’ mobility pattern is inevitable affected by
human social character. This paper presents a novel mobility model (HNGM) which combines
social character and Gauss-Markov process together. The performance analysis on this
mobility model is given and one famous and widely used mobility model (RWP) is chosen to
make comparison..
This document presents a mathematical framework for analyzing systems of interacting networks. The key points are:
1) The framework allows calculating the percolation threshold and component size distributions for systems of l interacting networks, taking into account connectivity both within and between networks.
2) Exact expressions are derived for the percolation threshold and applied to different degree distributions for two interacting networks.
3) The framework is applied to real-world systems involving communications networks and software networks to better understand their structure and function.
1. The document discusses a proposed technique called Fuzzy Based Improved Mutual Friend Crawling (Fmfc) for crawling online social networks. It aims to reduce bias introduced by the time taken for crawling the whole network.
2. The technique crawls all users within the same community first before moving to the next community, allowing researchers to selectively obtain users belonging to the same community. This is compared to existing mutual friend crawling.
3. The paper also provides a literature review of existing crawling techniques and studies of complex network properties relevant to community detection in networks. Future work in overlapping communities and performance evaluation on very large networks is discussed.
Distribution of maximal clique size of theIJCNCJournal
Our primary objective in this paper is to study the distribution of the maximal clique size of the vertices in complex networks. We define the maximal clique size for a vertex as the maximum size of the clique that the vertex is part of and such a clique need not be the maximum size clique for the entire network. We determine the maximal clique size of the vertices using a modified version of a branch-and-bound based exact algorithm that has been originally proposed to determine the maximum size clique for an entire network graph. We then run this algorithm on two categories of complex networks: One category of networks capture the evolution of small-world networks from regular network (according to the well-known Watts-Strogatz model) and their subsequent evolution to random networks; we show that the distribution of
the maximal clique size of the vertices follows a Poisson-style distribution at different stages of the evolution of the small-world network to a random network; on the other hand, the maximal clique size of the vertices is observed to be in-variant and to be very close to that of the maximum clique size for the entire network graph as the regular network is transformed to a small-world network. The second category
of complex networks studied are real-world networks (ranging from random networks to scale-free networks) and we observe the maximal clique size of the vertices in five of the six real-world networks to follow a Poisson-style distribution. In addition to the above case studies, we also analyze the correlation between the maximal clique size and clustering coefficient as well as analyze the assortativity index of the
vertices with respect to maximal clique size and node degree.
Community detection aims to identify groups of nodes in a network that are more densely connected internally than to the rest of the network. It can reveal properties of networks without privacy risks. While similar to clustering, community detection methods consider graph properties directly due to challenges from network data. Two recent methods are discussed - one based on shortest path betweenness to iteratively remove inter-community edges, and another based on optimizing modularity, a measure of community structure quality. Modularity can be computed using the eigenvectors of the modularity matrix.
Clustering Methods and Community Detection with NetworkX. A slide deck for the NTU Complexity Science Winter School.
For the accompanying iPython Notebook, visit: http://github.com/eflegara/NetStruc
Scalable Local Community Detection with Mapreduce for Large NetworksIJDKP
Community detection from complex information networks draws much attention from both academia and
industry since it has many real-world applications. However, scalability of community detection algorithms
over very large networks has been a major challenge. Real-world graph structures are often complicated
accompanied with extremely large sizes. In this paper, we propose a MapReduce version called 3MA that
parallelizes a local community identification method which uses the $M$ metric. Then we adopt an
iterative expansion approach to find all the communities in the graph. Empirical results show that for large
networks in the order of millions of nodes, the parallel version of the algorithm outperforms the traditional
sequential approach to detect communities using the M-measure. The result shows that for local community
detection, when the data is too big for the original M metric-based sequential iterative expension approach
to handle, our MapReduce version 3MA can finish in a reasonable time.
Towards a democratic, scalable, and sustainable digital future (a complex sys...Kolja Kleineberg
The document discusses a complex systems perspective on achieving a democratic, scalable and sustainable digital future. It summarizes research showing that digital diversity is possible but fragile, and that routing performance improves when individuals are active across multiple networks. The key conclusion is that an appropriate incentive system using cryptocurrency to reward routing could help sustain digital diversity, increase routing performance, and lead to a robust decentralized digital world.
The overwhelming success of online social networks, the key actors in the cosmos of the Web 2.0, has reshaped human interactions on a worldwide scale. To understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we discuss the impact of heterogeneity in network intrinsic fitnesses induced by the competition between an international network, like Facebook, and local services. To this end, we construct a 1:1000 scale model of the digital world enclosing the 80 countries with most Internet users. We show how inter-country social ties induce an increased intrinsic fitness of the international network. Under certain conditions this leads to the extinction of local networks whereas under different conditions local networks can persist and even dominate the international network completely. These findings provide new insights into the possibilities to preserve digital diversity.
Future of m2 m iot m2m forum cee - vienna - 9 june 2015 lrFuture Agenda
This document discusses perspectives on the future of machine-to-machine (M2M) communications and the Internet of Things (IoT). It summarizes insights from the 2010 Future Agenda program regarding trends in 2020 related to ubiquitous data access, digitization of all information, and predictive analytics enabled by IoT. Examples are provided of smart city collaborations between companies like Intel and San Jose and Cisco and Songdo. The Future Agenda 2.0 program expands on these insights through increased global engagement. Perspectives on a fully connected world by 2025 with intelligent networks and understanding previously unknown data are also presented.
TCS Innovation Forum - The Digital World in 2025 - 28 05 15Future Agenda
On 28th May we are running a min workshop at the London TCS Innovation Forum. This is looking how digital and data are changing society and this presentation is a starting point for that discussion.
Beyond Bitcoin, Beyond Blockchain, the Era of Decentralized Applications or D...Mehdi Tehrani
The document discusses the rise of cryptocurrencies and decentralized applications (DApps). It argues that we are entering a new era driven by DApps, which are applications that run on decentralized networks without centralized control. DApps have the potential for mass adoption due to features like decentralization, consensus-based validation, open source code, and internal digital assets or tokens. However, challenges include potential centralization of networks due to economies of scale, and risks from trading decentralized assets on centralized exchanges. Overall, the document frames the emerging cryptocurrency phenomenon in terms of a major technological shift enabled by DApps.
Smart cities | Smarter citizens Vienna - 25 Nov 2014 lrTim Jones
A keynote at the Zero Emission Cities Conference in Vienna focused on shifts in focus of smart cities. Key contrast is made between what is being embedded in city infrastructures to make them more intelligent and efficient vs. how people in cities can use, share and interpret data to make more intelligent decisions.
Talk is split into three parts:
What we say about the future of cities from the first Future Agenda programme in 2010
An overview of some of the key developments and collaborations that have taken place since
Some key questions that we see are being asked about citizen engagement that we will explore in the second future agenda programme in 2015
This presentation offers a brief overview on the Smart Cities topic, providing some data and some useful insights about why new kind of cities are needed and at the same time presenting some trends that boost the emergence of new urban paradigms.
Spatial patterns in evolutionary games on scale-free networks and multiplexesKolja Kleineberg
The document discusses evolutionary games on scale-free networks and multiplexes. It finds that cooperation can be sustained in metric clusters that form on scale-free networks. These metric clusters shield cooperators from surrounding defectors similar to spatial selection. The survival of metric clusters is favored when the network is less heterogeneous, has a higher clustering coefficient, and the clusters are larger. Similar clusters are also found for different games played on correlated multiplex networks.
Interplay between social influence and competitive strategical games in multi...Kolja Kleineberg
The document discusses the interplay between social influence and competitive strategic games on multiplex networks. It shows that an opinion dynamics model with pro-cooperation bias can transform a prisoner's dilemma game into a snowdrift game. Considering multiplex topology is important, as correlations between network layers can have an even bigger impact on cooperation than individual layer topologies alone. When similarity correlations are present between layers, cooperative clusters can form across both layers through self-organization.
Towards controlling evolutionary dynamics through network geometry: some very...Kolja Kleineberg
The document discusses how network geometry can control evolutionary dynamics through the formation of cooperating clusters. It presents examples showing how the placement of initial cooperators in metric space clusters versus randomly can influence whether cooperation emerges in evolutionary games and navigation processes on networks. The author suggests that network geometry may allow active control of evolutionary dynamics by strategically placing control agents based on the underlying geometry.
Geometric correlations mitigate the extreme vulnerability of multiplex networ...Kolja Kleineberg
The document discusses how geometric correlations between layers in multiplex networks can mitigate their vulnerability to targeted attacks. It finds that while degree correlations provide some robustness to random failures, they do not prevent catastrophic cascades under targeted attacks. However, geometric or similarity correlations, which place similar nodes close together in an underlying metric space representing each layer, can significantly increase robustness to targeted attacks. This effect is demonstrated through a model incorporating such correlations, as well as analyses of real-world multiplex networks that exhibit stronger geometric correlations.
A Proposed Algorithm to Detect the Largest Community Based On Depth LevelEswar Publications
The incredible rising of online networks show that these networks are complex and involving massive data.Giving a very strong interest to set of techniques developed for mining these networks. The clique problem is a well known NP-Hard problem in graph mining. One of the fundamental applications for it is the community detection. It helps to understand and model the network structure which has been a fundamental problem in several fields. In literature, the exponentially increasing computation time of this problem make the quality of these solutions is limited and infeasible for massive graphs. Furthermore, most of the proposed approaches are able to detect only disjoint communities. In this paper, we present a new clique based approach for fast and efficient overlapping
community detection. The work overcomes the short falls of clique percolation method (CPM), one of most popular and commonly used methods in this area. The shortfalls occur due to brute force algorithm for enumerating maximal cliques and also the missing out many vertices thatleads to poor node coverage. The proposed work overcome these shortfalls producing NMC method for enumerating maximal cliques then detects overlapping communities using three different community scales based on three different depth levels to assure high nodes coverage and detects the largest communities. The clustering coefficient and cluster density are used to measure the quality. The work also provide experimental results on benchmark real world network to
demonstrate the efficiency and compare the new proposed algorithm with CPM method, The proposed algorithm is able to quickly discover the maximal cliques and detects overlapping community with interesting remarks and findings.
This document summarizes two presentations about community detection in social media networks. The first presentation discusses using edge content, like image tags, to help identify communities in networks. The second focuses on leveraging interaction intensities on Twitter to detect communities that form around certain events over time. Both aim to improve on traditional methods that only consider network structure.
This document discusses community detection in social media and online networks. It defines communities as groups of densely interconnected nodes in a graph. It outlines various algorithms for detecting communities, including graph partitioning, k-clique detection, core decomposition, divisive algorithms based on edge centrality, and modularity maximization approaches. It also discusses local community detection methods and evaluation of community detection results.
MODELING SOCIAL GAUSS-MARKOV MOBILITY FOR OPPORTUNISTIC NETWORK csandit
Mobility is attracting more and more interests due to its importance for data forwarding
mechanisms in many networks such as mobile opportunistic network. In everyday life mobile
nodes are often carried by human. Thus, mobile nodes’ mobility pattern is inevitable affected by
human social character. This paper presents a novel mobility model (HNGM) which combines
social character and Gauss-Markov process together. The performance analysis on this
mobility model is given and one famous and widely used mobility model (RWP) is chosen to
make comparison..
This document presents a mathematical framework for analyzing systems of interacting networks. The key points are:
1) The framework allows calculating the percolation threshold and component size distributions for systems of l interacting networks, taking into account connectivity both within and between networks.
2) Exact expressions are derived for the percolation threshold and applied to different degree distributions for two interacting networks.
3) The framework is applied to real-world systems involving communications networks and software networks to better understand their structure and function.
1. The document discusses a proposed technique called Fuzzy Based Improved Mutual Friend Crawling (Fmfc) for crawling online social networks. It aims to reduce bias introduced by the time taken for crawling the whole network.
2. The technique crawls all users within the same community first before moving to the next community, allowing researchers to selectively obtain users belonging to the same community. This is compared to existing mutual friend crawling.
3. The paper also provides a literature review of existing crawling techniques and studies of complex network properties relevant to community detection in networks. Future work in overlapping communities and performance evaluation on very large networks is discussed.
Distribution of maximal clique size of theIJCNCJournal
Our primary objective in this paper is to study the distribution of the maximal clique size of the vertices in complex networks. We define the maximal clique size for a vertex as the maximum size of the clique that the vertex is part of and such a clique need not be the maximum size clique for the entire network. We determine the maximal clique size of the vertices using a modified version of a branch-and-bound based exact algorithm that has been originally proposed to determine the maximum size clique for an entire network graph. We then run this algorithm on two categories of complex networks: One category of networks capture the evolution of small-world networks from regular network (according to the well-known Watts-Strogatz model) and their subsequent evolution to random networks; we show that the distribution of
the maximal clique size of the vertices follows a Poisson-style distribution at different stages of the evolution of the small-world network to a random network; on the other hand, the maximal clique size of the vertices is observed to be in-variant and to be very close to that of the maximum clique size for the entire network graph as the regular network is transformed to a small-world network. The second category
of complex networks studied are real-world networks (ranging from random networks to scale-free networks) and we observe the maximal clique size of the vertices in five of the six real-world networks to follow a Poisson-style distribution. In addition to the above case studies, we also analyze the correlation between the maximal clique size and clustering coefficient as well as analyze the assortativity index of the
vertices with respect to maximal clique size and node degree.
Community detection aims to identify groups of nodes in a network that are more densely connected internally than to the rest of the network. It can reveal properties of networks without privacy risks. While similar to clustering, community detection methods consider graph properties directly due to challenges from network data. Two recent methods are discussed - one based on shortest path betweenness to iteratively remove inter-community edges, and another based on optimizing modularity, a measure of community structure quality. Modularity can be computed using the eigenvectors of the modularity matrix.
Clustering Methods and Community Detection with NetworkX. A slide deck for the NTU Complexity Science Winter School.
For the accompanying iPython Notebook, visit: http://github.com/eflegara/NetStruc
Scalable Local Community Detection with Mapreduce for Large NetworksIJDKP
Community detection from complex information networks draws much attention from both academia and
industry since it has many real-world applications. However, scalability of community detection algorithms
over very large networks has been a major challenge. Real-world graph structures are often complicated
accompanied with extremely large sizes. In this paper, we propose a MapReduce version called 3MA that
parallelizes a local community identification method which uses the $M$ metric. Then we adopt an
iterative expansion approach to find all the communities in the graph. Empirical results show that for large
networks in the order of millions of nodes, the parallel version of the algorithm outperforms the traditional
sequential approach to detect communities using the M-measure. The result shows that for local community
detection, when the data is too big for the original M metric-based sequential iterative expension approach
to handle, our MapReduce version 3MA can finish in a reasonable time.
Towards a democratic, scalable, and sustainable digital future (a complex sys...Kolja Kleineberg
The document discusses a complex systems perspective on achieving a democratic, scalable and sustainable digital future. It summarizes research showing that digital diversity is possible but fragile, and that routing performance improves when individuals are active across multiple networks. The key conclusion is that an appropriate incentive system using cryptocurrency to reward routing could help sustain digital diversity, increase routing performance, and lead to a robust decentralized digital world.
The overwhelming success of online social networks, the key actors in the cosmos of the Web 2.0, has reshaped human interactions on a worldwide scale. To understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we discuss the impact of heterogeneity in network intrinsic fitnesses induced by the competition between an international network, like Facebook, and local services. To this end, we construct a 1:1000 scale model of the digital world enclosing the 80 countries with most Internet users. We show how inter-country social ties induce an increased intrinsic fitness of the international network. Under certain conditions this leads to the extinction of local networks whereas under different conditions local networks can persist and even dominate the international network completely. These findings provide new insights into the possibilities to preserve digital diversity.
Future of m2 m iot m2m forum cee - vienna - 9 june 2015 lrFuture Agenda
This document discusses perspectives on the future of machine-to-machine (M2M) communications and the Internet of Things (IoT). It summarizes insights from the 2010 Future Agenda program regarding trends in 2020 related to ubiquitous data access, digitization of all information, and predictive analytics enabled by IoT. Examples are provided of smart city collaborations between companies like Intel and San Jose and Cisco and Songdo. The Future Agenda 2.0 program expands on these insights through increased global engagement. Perspectives on a fully connected world by 2025 with intelligent networks and understanding previously unknown data are also presented.
TCS Innovation Forum - The Digital World in 2025 - 28 05 15Future Agenda
On 28th May we are running a min workshop at the London TCS Innovation Forum. This is looking how digital and data are changing society and this presentation is a starting point for that discussion.
Beyond Bitcoin, Beyond Blockchain, the Era of Decentralized Applications or D...Mehdi Tehrani
The document discusses the rise of cryptocurrencies and decentralized applications (DApps). It argues that we are entering a new era driven by DApps, which are applications that run on decentralized networks without centralized control. DApps have the potential for mass adoption due to features like decentralization, consensus-based validation, open source code, and internal digital assets or tokens. However, challenges include potential centralization of networks due to economies of scale, and risks from trading decentralized assets on centralized exchanges. Overall, the document frames the emerging cryptocurrency phenomenon in terms of a major technological shift enabled by DApps.
Smart cities | Smarter citizens Vienna - 25 Nov 2014 lrTim Jones
A keynote at the Zero Emission Cities Conference in Vienna focused on shifts in focus of smart cities. Key contrast is made between what is being embedded in city infrastructures to make them more intelligent and efficient vs. how people in cities can use, share and interpret data to make more intelligent decisions.
Talk is split into three parts:
What we say about the future of cities from the first Future Agenda programme in 2010
An overview of some of the key developments and collaborations that have taken place since
Some key questions that we see are being asked about citizen engagement that we will explore in the second future agenda programme in 2015
This presentation offers a brief overview on the Smart Cities topic, providing some data and some useful insights about why new kind of cities are needed and at the same time presenting some trends that boost the emergence of new urban paradigms.
This document discusses the need for global cooperation and connection in the digital media and entertainment industries. It argues that countries and cultures should work together not just as observers of technological advances but as active participants. To truly communicate information across boundaries requires considering different perspectives and ensuring accessibility regardless of economic situation. The document proposes strengthening regional networks to distribute information more widely and prevent any single entity from monopolizing information control, while still collaborating with larger networks. This would help maintain information quality and authenticity as it spreads more broadly. Overall, the document advocates for low-cost technology access, ongoing education, and global exchange to connect people worldwide through information and communication.
Joachim Stroh: Hypha DAO, the 3rd generation of DAOsEdunomica
Joachim Stroh: Hypha DAO, the 3rd generation of DAOs
DAO Camp 2023 Winter
Website: https://daocamp.org
Youtube: https://www.youtube.com/channel/UCeHtPZ_ZLZ-nHFMUCXY81RQ
FB: https://www.facebook.com/DAO-Camp-102442798988862/
The document provides an overview and analysis of leading smart city projects in the United States. It identifies Portland and Seattle as initial cities for a field trip by a Finnish delegation due to their high scores across metrics relevant to smart city development. Relevant smart city cases from Oregon and Washington are highlighted, including systems modeling in Portland, sustainability tools in Tacoma, and the Living Building Challenge framework. The document proposes broadening the field trip to include Anchorage, representing the Cascadia region of North America as a logical place to start Finnish-American smart city networking.
This document summarizes research on the interplay between the network structure and market effects in Bitcoin. It provides analysis of the Bitcoin transaction network growth over time. Key findings include:
- The in-degree and out-degree distributions follow power laws with exponents around -2.
- The Gini coefficient of the degree and balance distributions increases over time, showing rich get richer behavior.
- The clustering coefficient and degree correlations decrease over time as the network matures.
- Higher degree nodes tend to connect to lower degree nodes.
- Nonlinear preferential attachment leads to stretched exponential degree distributions.
- Balance distributions also follow a power law with an exponent around -2.
- Structural changes in
Citizenship in an Exponential Era - David BraySUCanadaSummit
The session focused on what the future looks like if exponential trends continue their impact on governance, security and stability in a networked era and what new strategies private and public sector leaders will need to employ to be effective.
ABSTRACT : The Internet of Things (IoT) describes a special network with many physical things which have
embedded sensors, software, and other technologies. These devices, such as traffic lights, vehicles, home alarms
and other objects are connected for the purpose of exchanging data with other devices and systems over the
internet. The IoT technology is utilized by Smart Cities, to offer many benefits to the state in conjunction with
LP-WAN. In this assignment we will refer to LP-WAN in wireless communication technology and the three
famous technologies that support this technology, which are SigFox, LoRaWAN and NB-IoT and how to apply
in the smart cities. In addition, we will report a threat that smart cities face nowadays, and specifically we will
describe what the DDoS threat is and how it can affect the network of smart cities. Finally, we describe a recent
incident DDoS attack, approaching the incident which is known Stuxnet
Key Words: LPWAN, SigFox, NB-IoT, LoRa, Smart Cities, DDoS, Stuxnet
Sheldon Renan's presentation at eComm 2008eComm2008
The document discusses the concept of "netness", which refers to the emerging state of ubiquitous connectivity where lives and systems are increasingly interconnected. As connectivity becomes more prevalent, networks transform into fields and lives become more entangled. This shift represents a fourth state of connectivity beyond being loosely, closely or embedded connected. When all things can connect, safety, capability and opportunity increase, making connectivity vital for optimizing products, business models and governance. Moving forward, further study of connectivity's value and focus on pervasive networks is needed.
IWCI21: Distributed Ledgers for Distributed Edgeeichhorl
This document discusses the challenges of using distributed ledger technology (DLT) at the network edge. It finds that DLT is currently ill-suited for edge computing due to high latency and lack of locality. Permissioned and localized DLT designs may be necessary to enable edge use cases. The document also describes a blockchain emulator called NEBULA that can evaluate DLT performance under different network parameters and consensus protocols.
Semelhante a Towards a democratic, scalable, and sustainable digital future (20)
Securing BGP: Operational Strategies and Best Practices for Network Defenders...APNIC
Md. Zobair Khan,
Network Analyst and Technical Trainer at APNIC, presented 'Securing BGP: Operational Strategies and Best Practices for Network Defenders' at the Phoenix Summit held in Dhaka, Bangladesh from 23 to 24 May 2024.
HijackLoader Evolution: Interactive Process HollowingDonato Onofri
CrowdStrike researchers have identified a HijackLoader (aka IDAT Loader) sample that employs sophisticated evasion techniques to enhance the complexity of the threat. HijackLoader, an increasingly popular tool among adversaries for deploying additional payloads and tooling, continues to evolve as its developers experiment and enhance its capabilities.
In their analysis of a recent HijackLoader sample, CrowdStrike researchers discovered new techniques designed to increase the defense evasion capabilities of the loader. The malware developer used a standard process hollowing technique coupled with an additional trigger that was activated by the parent process writing to a pipe. This new approach, called "Interactive Process Hollowing", has the potential to make defense evasion stealthier.
Honeypots Unveiled: Proactive Defense Tactics for Cyber Security, Phoenix Sum...APNIC
Adli Wahid, Senior Internet Security Specialist at APNIC, delivered a presentation titled 'Honeypots Unveiled: Proactive Defense Tactics for Cyber Security' at the Phoenix Summit held in Dhaka, Bangladesh from 23 to 24 May 2024.
9. vision of our digital future.
We need a
democratic,
scalable,
sustainable
10. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Self-organization of the digital world can
create and sustain a desirable digital futurePartFocus
Democratic Scalable Sustainable
Digital diversity
(no monopolies)
Efficient search
and navigation
Robust/resilient to
perturbations
Decentralization
(people in control)
Only rely on
local knowledge
Ability to recover
from losses
Digital ecology Geometry of
multiplexes
Social Bitcoin
incentive
10
11. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Self-organization of the digital world can
create and sustain a desirable digital futurePartFocus
Democratic Scalable Sustainable
Digital diversity
(no monopolies)
Efficient search
and navigation
Robust/resilient to
perturbations
Decentralization
(people in control)
Only rely on
local knowledge
Ability to recover
from losses
Digital ecology Geometry of
multiplexes
Social Bitcoin
incentive
10
12. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Self-organization of the digital world can
create and sustain a desirable digital futurePartFocus
Democratic Scalable Sustainable
Digital diversity
(no monopolies)
Efficient search
and navigation
Robust/resilient to
perturbations
Decentralization
(people in control)
Only rely on
local knowledge
Ability to recover
from losses
Digital ecology Geometry of
multiplexes
Social Bitcoin
incentive
10
14. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Evolution of isolated online social networks unfolds
on top of underlying social structure
Online social
network layer
Traditional contact
network layer
Active
Online & offline
Passive
Online & offline
Susceptible
Only offline
Mass media activation Viral activation
Deactivation Viral reactivation
12
15. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Digital ecosystem is formed by multiple networks
competing for the attention of individuals
OSN 2
OSN 1
Underl.
network
Active
Passive
Susceptible
Partial
states}
Virality share
distribution
between OSNs
λi = ωi(ρa)λ
Rich-get-richer
more active
networks obtain
higher share
Here: ωi = [ρa
i ]σ/
∑
j[ρa
j]σ
σ: activity affinity
13
16. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Digital ecosystem is formed by multiple networks
competing for the attention of individuals
OSN 2
OSN 1
Underl.
network
Active
Passive
Susceptible
Partial
states}
Virality share
distribution
between OSNs
λi = ωi(ρa)λ
Rich-get-richer
more active
networks obtain
higher share
Here: ωi = [ρa
i ]σ/
∑
j[ρa
j]σ
σ: activity affinity
Does rich-get-richer effect always lead to the
domination of a single network?
13
17. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Coexistence is possible in a certain parameter region
despite the rich-get-richer mechanism
Stable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
σ
ρ1,2
a
14
18. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Coexistence is possible in a certain parameter region
despite the rich-get-richer mechanism
Stable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
σ
ρ1,2
a
Coexistence
despite rich-get-richer
14
19. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Coexistence is possible in a certain parameter region
despite the rich-get-richer mechanism
Stable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
σ
ρ1,2
a
Coexistence
despite rich-get-richer
Digital diversity
is fragile
14
20. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Digital diversity is possible but fragile
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
15
21. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Digital diversity is possible but fragile
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
Scalable
15
23. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Hidden metric spaces underlying real complex networks
provide a fundamental explanation of their observed topologies
Nature Physics 5, 74–80 (2008)
17
24. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Hidden metric spaces underlying real complex networks
provide a fundamental explanation of their observed topologies
We can infer the coordinates of nodes embedded in
hidden metric spaces.
17
25. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Constituent network layers of real multiplex systems
are embedded separately into hidden hyperbolic space
Internet IPv4 network Internet IPv6 network
18
26. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Constituent network layers of real multiplex systems
are embedded separately into hidden hyperbolic space
Internet IPv4 network Internet IPv6 network
Are coordinates of same nodes in different layers
correlated?
18
27. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Radial and angular coordinates are correlated
between different layers in many real multiplexes
0
π
2 π
θ1
0
π
2 π
θ2
50
100
150
200
19
28. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Radial and angular coordinates are correlated
between different layers in many real multiplexes
0
π
2 π
θ1
0
π
2 π
θ2
50
100
150
200
How do discovered geometric correlations affect
search and navigation with local knowledge?
19
29. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Mutual greedy routing allows efficient navigation
using several network layers with only local knowledge
Forward message
to contact closest
to target in metric
space
Messages switch
layers if contact has
a closer neighbor in
another layer
Delivery fails
if message runs into
a loop (define
success rate P)
20
30. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Geometric correlations determine the improvement of
mutual greedy routing by increasing the number of layers
0.0 0.2 0.4 0.6 0.8 1.0
0.2
0.4
0.6
0.8
1.0
Hyperbolic routing
0.980
0.985
0.990
0.995
P
1 2 3 4
0
2
4
6
Layers
Mitigationfactor
opt. correlated
uncorrelated
Angular correlations
Radialcorrelations
Reduction of failure rate
21
31. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Geometric correlations determine the improvement of
mutual greedy routing by increasing the number of layers
0.0 0.2 0.4 0.6 0.8 1.0
0.2
0.4
0.6
0.8
1.0
Hyperbolic routing
0.980
0.985
0.990
0.995
P
1 2 3 4
0
2
4
6
Layers
Mitigationfactor
opt. correlated
uncorrelated
Angular correlations
Radialcorrelations
Reduction of failure rate
Routing is perfected by using many networks
simultaneously if correlations are present.
21
32. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Diversity improves performance of search and navigation
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
22
33. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Diversity improves performance of search and navigation
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
22
34. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Diversity improves performance of search and navigation
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
Sustainable
22
35. Could a »Social Bitcoin« sustain a
democratic digital world?
36. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Cryptocurrency »Social Bitcoins« are mined
by users performing routing in the Internet
Individuals
perform routing
instead of service
providers
Routing
information is
rewarded by Social
Bitcoins
Payoff
depends on routing
success &
reputation
24
37. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Incentive to mine Social Bitcoins causes tendency
to be active in several networks simultaneously
Qualified Money
t
o
route
activein
m
any networks
Optim
izes strategy:
Inc
entive
Sustains
digital dive
rsity
Increasesro
uting
perform
a
nce
Exchangeable
Social Bitcoin
+Reputation
25
38. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Tendency to be active in several networks simultaneously
influences distribution of attention between networks
Virality share
distribution
between OSNs
λi = ωi(ρa)λ
Rich-get-richer
more active
networks obtain
higher share
Social Bitcoins
tendency to use
several networks
simultaneously
ωi(ρa
) =
[ρa
i ]σ
∑nl
j=1
[
ρa
j
]σ
rich-get-richer
+ ξ(⟨ρa
⟩ − ρa
i )
Social Bitcoin incentive
ξ proportional to price of Social Bitcoins
26
39. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
Social Bitcoin incentive can make digital diversity robust
but only if its value is sufficiently high
ξ = 0.2 ξ = 1.0
Stable
Unstable
0.5 1.0 1.5 2.0
0.0
0.2
0.4
0.6
0.8
σ
ρ1,2
a
Unstable FP
Stable FP
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
ρ1
a
ρ2
a
σ=0.75
Unstable FP
Stable FP
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
ρ1
a
ρ2
a
σ=1.5
Stable
Unstable
1.5 2.0 2.5 3.0
0.0
0.2
0.4
0.6
0.8
σ
ρ1,2
a
Unstable FP
Stable FP
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
ρ1
a
ρ2
a
σ=1.75
Unstable FP
Stable FP
0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
ρ1
a
ρ2
a
σ=2.5
27
40. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Multidimensional incentives could lead to sustainability
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
28
41. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Multidimensional incentives could lead to sustainability
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
28
42. We need a Democratic (diverse) Scalable (decentralized) Sustainable (robust) Digital Future
A democratic, scalable, and sustainable digital future:
Multidimensional incentives could lead to sustainability
to route
strategy
Optimizes
Incentive
Sustains
digital diversity
Increases routing
performance
Social Bitcoin
+ReputationStable
Unstable
0.50 0.75 1.00 1.25 1.50
0.00
0.25
0.50
0.75
0.00
0.25
0.50
0.75
Bifurcation diagram
ρ1
a
0.0 0.5 1.0 1.5
0.50
0.75
σ
σ
ρ1,2
a
FrameworkResultFocus
Democratic
PRX 4, 031046
Sci. Rep. 5, 10268
Sci. Rep. 6, 25116
Scalable Sustainable
Is digital diversity
possible?
Search and navigation
with local knowledge
Incentives sustain diverse
decentralized digital world
Network evolution &
competition
Geometric correlations,
mutual greedy routing
Digital diversity is
possible but fragile
Routing perfected by
using many networks
Digital diversity becomes
robust & routing improves
Refs
Nature Physics
doi:10.1038/nphys3812
arXiv:1604.08168
Social Bitcoins as incen-
tive to route information
28
47. Evolution of the Digital Society reveals Balance between Mass
Media and Viral Influence
Physical Review X (4) 031046
K.-K. Kleineberg, M. Boguña
Digital Ecology: Coexistence and Domination among Interacting
Networks
Sci. Rep. 5, 10268
K.-K. Kleineberg, M. Boguña
Competition between global and local online social networks
Sci. Rep. 6, 25116
K.-K. Kleineberg, M. Boguña
Hidden geometric correlations in real multiplex networks
Nature Physics, doi: 10.1038/NPHYS3782, URL: rdcu.be/i9iO
K.-K. Kleineberg, M. Boguñá, M. A. Serrano, F. Papadopoulos
A »Social Bitcoin« could sustain a democratic digital world
arXiv:1604.08168 or ssrn.com/abstract=2771326
K.-K. Kleineberg, D. Helbing
48. M. Boguñá, M. A. Serrano, F. Papadopoulos
Collaborators:
49. Credits:
In the Distance: Angus MacRae
Obsolete hardware David
Hayward
Cables: jerry john
Surveillance: Jon Olav Eikenes
Team icon: Joshua Jones
Compass: Creative Stall
Bitcoin: Mourad Mokrane, RU
Megaphone: Alex Auda Samora
Biohazard: Shailendra Chouhan
Money: Lemon Liu
Layer icon: Mentaltoy
Loop: useiconic.com
Connected: Muharrem Fevzi
Çelik
Multi-dimensional incentive:
Gregor rešnar
Reputation stars: Guilhem
Internet router: Thomas Uebe
Individual: lastspark
Flower: Nishanth Jois
50. Let's keep in touch!
Kaj Kolja Kleineberg:
• kajkoljakleineberg@gmail.com
• @KoljaKleineberg
• koljakleineberg.wordpress.com