arXiv subjects

Bernardo A. Huberman

Publications and source records attributed to Bernardo A. Huberman.

At least 91 records · Page 5Linked to original sources

arXiv2003

Email as Spectroscopy: Automated Discovery of Community Structure within Organizations

We describe a methodology for the automatic identification of communities of practice from email logs within an organization. We use a betweeness centrality algorithm that can rapidly find communities within a graph representing information flows. We apply this algorithm to an email corpus of nearly one million messages collected over a two-month span, and show that the method is effective at identifying true communities, both formal and informal, within these scale-free graphs. This approach also enables the identification of leadership roles within the communities. These studies are complemented by a qualitative evaluation of the results in the field.

cond-mat.stat-mech↗

arXiv2002

Finding Communities of Related Genes

We present an automated method of identifying communities of functionally related genes from the biomedical literature. These communities encapsulate human gene and protein interactions and identify groups of genes that are complementary in their function. We use graphs to represent the network of gene cooccurrences in articles mentioning particular keywords, and find that these graphs consist of one giant connected component and many small ones. In addition, the vertex degree distribution of the graphs follows a power law, whose exponent we determine. We then use an algorithm based on betweenness centrality to identify community structures within the giant component. The different structures are then aggregated into a final list of communities, whose members are weighted according to how strongly they belong to them. Our method is efficient enough to be applicable to the entire Medline database, and yet the information it extracts is significantly detailed, applicable to a particular problem, and interesting in and of itself. We illustrate the method in the case of colon cancer and demonstrate important features of the resulting communities.

cond-mat.stat-mech↗

arXiv2002

Eliminating Public Knowledge Biases in Small Group Predictions

We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings. A two stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals' public information. A nonlinear aggregation of their decisions then allows for the calculation of the probability of the future outcome of an uncertain event, which can then be compared to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism outperforms both the imperfect market and the best of the participants. .

cond-mat.stat-mech↗

arXiv2002

Local Search in Unstructured Networks

We review a number of message-passing algorithms that can be used to search through power-law networks. Most of these algorithms are meant to be improvements for peer-to-peer file sharing systems, and some may also shed some light on how unstructured social networks with certain topologies might function relatively efficiently with local information. Like the networks that they are designed for, these algorithms are completely decentralized, and they exploit the power-law link distribution in the node degree. We demonstrate that some of these search algorithms can work well on real Gnutella networks, scale sub-linearly with the number of nodes, and may help reduce the network search traffic that tends to cripple such networks.

cond-mat.dis-nn↗

arXiv2001

Forecasting Uncertain Events with Small Groups

We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their predictions, we are able to assess the probability of the future outcome of an uncertain event and compare it to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism vastly outperforms both the imperfect market and the best of the participants.

cond-mat.stat-mech↗

arXiv2000

Competitive Dynamics of Web Sites

We present a dynamical model of web site growth in order to explore the effects of competition among web sites and to determine how they affect the nature of markets. We show that under general conditions, as the competition between sites increases, the model exhibits a sudden transition from a regime in which many sites thrive simultaneously, to a "winner take all market" in which a few sites grab almost all the users, while most other sites go nearly extinct. This prediction is in agreement with recent measurements on the nature of electronic markets.

nlin.CD↗

arXiv2000

Comment to "Emergence of Scaling in Random Networks" (cond-mat/9910332)

A recent paper "Emergence of scaling in random networks" (cond-mat/9910332) by Barabasi and Albert proposes a growth mechanism to produce a stationary scale free distribution of the number of edges per node in large networks such as the Web. The Barabasi-Albert model predicts that older vertices acquire new edges at the expense of younger ones, giving a strong correlation between the time a vertex is introduced and the number of edges it has. We present data from the Web showing that there is no such correlation and point to an alternative growth model which produces the correct relationship between the age of a site and the number of links it has.

cond-mat.dis-nn↗

arXiv2000

Optimizing Traffic in Virtual and Real Space

We show how optimization methods from economics known as portfolio strategies can be used for minimizing download times in the Internet and travel times in freeway traffic. While for Internet traffic, there is an optimal restart frequency for requesting data, freeway traffic can be optimized by a small percentage of vehicles coming from on-ramps. Interestingly, the portfolio strategies can decrease the average waiting or travel times, respectively, as well as their standard deviation (``risk''). In general, portfolio strategies are applicable to systems, in which the distribution of the quantity to be optimized is broad.

cond-mat.stat-mech↗

arXiv1999

Economics-Based Optimization of Unstable Flows

As an example for the optimization of unstable flows, we present an economics-based method for deciding the optimal rates at which vehicles are allowed to enter a highway. It exploits the naturally occuring fluctuations of traffic flow and is flexible enough to adapt in real time to the transient flow characteristics of road traffic. Simulations based on realistic parameter values show that this strategy is feasible for naturally occurring traffic, and that even far from optimality, injection policies can improve traffic flow. Moreover, the same method can be applied to the optimization of flows of gases and granular media.

cond-mat.stat-mech↗

arXiv1999

Restart Strategies and Internet Congestion

We recently presented a methodology for quantitatively reducing the risk and cost of executing electronic transactions in a bursty network environment such as the Internet. In the language of portfolio theory, time to complete a transaction and its variance replace the expected return and risk associated with a security, whereas restart times replace combinations of securities. While such a strategy works well with single users, the question remains as to its usefulness when used by many. By using mean field arguments and agent-based simulations, we determine that a restart strategy remains advantageous even if everybody uses it.

chao-dyn↗

arXiv1999

Evolutionary Dynamics of the World Wide Web

We present a theory for the growth dynamics of the World Wide Web that takes into account the wide range of stochastic growth rates in the number of pages per site, as well as the fact that new sites are created at different times. This leads to the prediction of a universal power law in the distribution of the number of pages per site which we confirm experimentally by analyzing data from large crawls made by the search engines Alexa and Infoseek. The existence of this power law not only implies the lack of any length scale for the Web, but also allows one to determine the expected number of sites of any given size without having to exhaustively crawl the Web.

cond-mat.stat-mech↗

arXiv1999

Coherent Moving States in Highway Traffic (Originally: Moving Like a Solid Block)

Recent advances in multiagent simulations have made possible the study of realistic traffic patterns and allow to test theories based on driver behaviour. Such simulations also display various empirical features of traffic flows, and are used to design traffic controls that maximise the throughput of vehicles in heavily transited highways. In addition to its intrinsic economic value, vehicular traffic is of interest because it may throw light on some social phenomena where diverse individuals competitively try to maximise their own utilities under certain constraints. In this paper, we present simulation results that point to the existence of cooperative, coherent states arising from competitive interactions that lead to a new phenomenon in heterogeneous highway traffic. As the density of vehicles increases, their interactions cause a transition into a highly correlated state in which all vehicles practically move with the same speed, analogous to the motion of a solid block. This state is associated with a reduced lane changing rate and a safe, high and stable flow. It disappears as the vehicle density exceeds a critical value. The effect is observed in recent evaluations of Dutch traffic data.

cond-mat.stat-mech↗

arXiv1998

Optimizing Traffic Flow

We present an economics-based method for deciding the optimal rates at which vehicles are allowed to enter a highway. The method exploits the naturally occuring fluctuations of traffic flow and is flexible enough to adapt in real time to the transient flow characteristics of road traffic. Simulations based on realistic parameter values show that this strategy is feasible for naturally occuring traffic, and that even far from optimality, injection policies can improve traffic flow. Our results also allow a better understanding of the high flows observed in ``synchronized'' congested traffic close to ramps.

cond-mat.stat-mech↗

arXiv1998

Novelty and Social Search in the World Wide Web

The World Wide Web is fast becoming a source of information for a large part of the world's population. Because of its sheer size and complexity users often resort to recommendations from others to decide which sites to visit. We present a dynamical theory of recommendations which predicts site visits by users of the World Wide Web. We show that it leads to a universal power law for the number of users that visit given sites over periods of time, with an exponent related to the rate at which users discover new sites on their own. An extensive empirical study of user behavior in the Web that we conducted confirms the existence of this law of influence while yielding bounds on the rate of novelty encountered by users.

cs.MA↗

arXiv1997

Power Markets for Controlling Smart Matter

Embedding microscopic sensors, computers and actuators into materials allows physical systems to actively monitor and respond to their environments. This leads to the possibility of creating smart matter, i.e., materials whose properties can be changed under program control to suit varying constraints. A key difficulty in realizing the potential of smart matter is developing the appropriate control programs. We present a market-based multiagent solution to the problem of maintaining a physical system near an unstable configuration, a particularly challenging application for smart matter. This market control leads to stability by focussing control forces in those parts of the system where they are most needed. Moreover, it does so even when some actuators fail to work and without requiring the agents to have a detailed model of the physical system.

cond-mat↗

arXiv1996

Controlling Smart Matter

Smart matter consists of many sensors, computers and actuators embedded within materials. These microelectromechanical systems allow properties of the materials to be adjusted under program control. In this context, we study the behavior of several organizations for distributed control of unstable physical systems and show how a hierarchical organization is a reasonable compromise between rapid local responses with simple communication and the use of global knowledge. Using the properties of random matrices, we show that this holds not only in ideal situations but also when imperfections and delays are present in the system. We also introduce a new control organization, the multihierarchy, and show it is better than a hierarchy in achieving stability. The multihierarchy also has a position invariant response that can control disturbances at the appropriate scale and location.

cond-mat↗

arXiv1995

The Instability of Markets

Recent developments in the global liberalization of equity and currency markets, coupled to advances in trading technologies, are making markets increasingly interdependent. This increased fluidity raises questions about the stability of the international financial system. In this paper, we show that as couplings between stable markets grow, the likelihood of instabilities is increased, leading to a loss of general equilibrium as the system becomes increasingly large and diverse.

adap-org↗

arXiv1994

Communities of Practice: Performance and Evolution

We present a detailed model of collaboration in communities of practice and we examine its dynamical consequences for the group as a whole. We establish the existence of a novel mechanism that allows the community to naturally adapt to growth, specialization, or changes in the environment without the need for central controls. This mechanism relies on the appearance of a dynamical instability that initates an exploration of novel interactions, eventually leading to higher performance for the community as a whole.

adap-org↗