Graph structure in the web

Bröder, Arndt; Kumar, Rajiv; Maghoul, Farzin; Raghavan, Prabhakar; Rajagopalan, Sridhar; Stata, Raymie; Tomkins, Andrew; Wiener, Joshua

doi:10.1515/9781400841356.183

Cited by 153 publications

(222 citation statements)

References 0 publications

Supporting

Mentioning

213

Contrasting

Unclassified

Order By: Relevance

“…The remaining disconnected components (DCs) are smaller components for which the same is true. In empirical studies, the GWCC is often found to be several orders of magnitude larger than any of the DCs [27].…”

Section: Componentsmentioning

confidence: 99%

The topology of the federal funds market

Bech

Atalay

2010

Physica A: Statistical Mechanics and its Applications

282

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in WO R K I N G PA PE R S E R I E S N O 98 6 / D E C E M B E R 20 0 8In 2008 all ECB publications feature a motif taken from the 10 banknote. provided an opportunity for participating central bank experts to exchange views and foster debate, also in interaction with international organizations and academic institutions. The first day of the workshop addressed issues related to the macro-perspective of the money market, drawing on the experiences of a large number of countries. The second day adopted a micro-perspective on the money market, looking in particular at trading behaviour in the overnight money market and its implications for the evolution of spreads. THE TOPOLOGY OF THE FEDERALA first version of this paper was presented at this workshop. The papers presented at the time of the workshop did not consider the potential implications of the financial turmoil for the results of the paper, given that the tensions in money markets emerged in August 2007. The published version of these papers represents an update of the original paper, which incorporates the discussion which took place at the workshop and in most cases a discussion on the developments in the money markets since August 2007. ECB Working Paper Series No 986December 2008 Abstract 4

show abstract

Section: Componentsmentioning

confidence: 99%

The topology of the federal funds market

Bech

Atalay

2010

Physica A: Statistical Mechanics and its Applications

282

View full text Add to dashboard Cite

show abstract

“…Figure 2 shows the same growth for the social network created from the U Alberta key server data. We found that the large world of the U Alberta key server key-ring behaves in a manner similar to the bow-tie structure observed with the world wide web [11]. This bow-tie is composed of a core "knot" of relationships in the middle.…”

Section: Gpg and Pgpsupporting

confidence: 56%

Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings

Warren

Wilkinson

Warnecke³

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Social networks are the focus of a large body of research. A number of popular email encryption tools make use of online directories to store public key information. These can be used to build a social network of people connected by email relationships. Since these directories contain creation and expiration time-stamps, the corresponding network can be built and analysed dynamically. At any given point, a snapshot of the current state of the model can be observed and traditional metrics evaluated and compared with the state of the model at other times.We show that, with this described data set, simple traditional predictive measures do vary with time. Moreover, singular events pertinent to the participants in the social network (such as conferences) can be correlated with or implied by significant changes in these measures. This provides evidence that the dynamic behaviour of social networks should not be ignored, either when analysing a real model or when attempting to generate a synthetic model.

show abstract

“…If γ > 2 then γ = 1 + z/a, which agrees with (5) for the undirected process. To see this put z = (1 + c)/(1 − c) − 1 and a = c. If 1 < γ ≤ 2 then γ = 1 + (z + 1)/(a + 1), and when z = 0 (stationary process) this agrees with (6) for the directed process. Dorogovtsev and Mendes also present substantial empirical results for many networks, whose relevance is as follows.…”

Section: Introductionmentioning

confidence: 61%

“…the one studied in this paper, the power law for in-degree is above 2 when f (t) = m constant, and below 2 when f (t) → ∞. The power law for in-degree of the World Wide Web in 1999 was estimated at 2.1 ( [6]). As this is close to 2, the authors of [13] ponder the evidence for accelerating growth in the Web.…”

Section: Introductionmentioning

confidence: 64%

Scale‐free graphs of increasing degree

Cooper¹,

Prałat²

2011

Random Struct Algorithms

View full text Add to dashboard Cite

We study a scale-free random graph process in which the number of edges added at each step increases. This differs from the standard model in which a fixed number, m, of edges are added at each step.Let f (t) be the number of edges added at step t. In the standard scale-free model, f (t) = m constant, whereas in this paper we consider f (t) = [t c ], c > 0. Such a graph process, in which the number of edges grows non-linearly with the number of vertices is said to have accelerating growth.We analyze both an undirected and a directed process. The power law of the degree sequence of these processes exhibits widely differing behaviour.For the undirected process, the terminal vertex of each edge is chosen by preferential attachment based on vertex degree. When f (t) = m constant, this is the standard scalefree model, and the power law of the degree sequence is 3. When f (t) = [t c ], c < 1, the degree sequence of the process exhibits a power law with parameter x = (3 − c)/(1 − c). As c → 0, x → 3, which gives a value of x = 3, as in standard scale-free model. Thus no more slowly growing monotone function f (t) alters the power law of this model away from x = 3. When c = 1, so that f (t) = t, the expected degree of all vertices is t, the vertex degree is concentrated, and the degree sequence does not have a power law.For the directed process, the terminal vertex is chosen proportional to in-degree plus an additive constant, to allow the selection of vertices of in-degree zero. For this process when f (t) = m is constant, the power law of the degree sequence is x = 2 + 1/m. When f (t) = [t c ], c > 0, the power law becomes x = 1 + 1/(1 + c), which naturally extends the power law to (1,2].

show abstract

Graph structure in the web

Cited by 153 publications

References 0 publications

The topology of the federal funds market

The topology of the federal funds market

Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings

Scale‐free graphs of increasing degree

Contact Info

Product

Resources

About