Sune Lehmann

Technical University of Denmark | DTU · Department of Informatics and Mathematical Modelling

Many systems, from power grids and the internet, to the brain and society, can be modeled using networks of coupled overlapping modules. The elements of these networks perform individual and collective tasks such as generating and consuming electrical load or transmitting data. We study the robustness of these systems using percolation theory: a ra...

Many complex systems, from power grids and the internet, to the brain and society, can be modeled using modular networks. Modules, densely interconnected groups of elements, often overlap due to elements that belong to multiple modules. The elements and modules of these networks perform individual and collective tasks such as generating and consumi...

Every second, the thoughts and feelings of millions of people across the world are recorded in the form of 140-character tweets using Twitter. However, despite the enormous potential presented by this remarkable data source, we still do not have an understanding of the Twitter population itself: Who are the Twitter users? How representative of the...

Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. One crucial step when studying the structure and dynamics of networks is to identify communities: groups of related nodes that correspond to functional subunits such as protei...

A report from the International Mathematical Union (IMU) in cooperation with the International Council of Industrial and Applied Mathematics (ICIAM) and the Institute of Mathematical Statistics (IMS)

Identifying modular network structure is generally a problem of finding the correct community membership of each node in a network. An alternative approach, clustering links, naturally accounts for real world characteristics such as strong community overlap, multi-partite structure, and hierarchical organization. By introducing a pair-wise link sim...

This exploratory study investigates the bipartite network of articles linked by common editors in Wikipedia, 'The Free Encyclopedia that Anyone Can Edit'. We use the articles in the categories (to depth three) of Physics and Philosophy and extract and focus on significant editors (at least 7 or 10 edits per each article). We construct a bipartite n...

We propose a new viewpoint for the problem of community detection in complex networks. Rather than defining a community as a set of densely interconnected nodes, we define a community as a set of (related) links. We show how this alternative viewpoint incorporates significant aspects including overlapping communities. A quantitative framework for e...

Modular and hierarchical organization are two of the most important organizing principles observed in many complex networks. It has often been assumed that detecting a hierarchy also implies finding modular struc-ture. However, highly overlapping community structure, present in many real networks including social and biological networks, interferes...

Networks in nature possess a remarkable amount of structure. Via a series of data-driven discoveries, the cutting edge of network science has recently progressed from positing that the random graphs of mathematical graph theory might accurately describe real networks to the current viewpoint that networks in nature are highly complex and structured...

Condensing the work of any academic scientist into a one-dimensional indicator of scientific performance is a difficult problem. Here, we employ Bayesian statistics to analyze several different indicators of scientific performance. Specifically, we determine each indicator’s ability to discriminate between scientific authors. Using scaling argument...

We present a method for detecting communities in bipartite networks. Based on an extension of the k -clique community detection algorithm, we demonstrate how modular structure in bipartite networks presents itself as overlapping bicliques. If bipartite information is available, the biclique community detection algorithm retains all of the advantage...

Eine wichtige Frage in den Kunstwissenschaften betrifft die Definition oder Entstehung des Kanon, d.h. der Menge wichtigster Objekte, die jeder in einem bestimmten Gebiet kennt oder vermeintlich kennen sollte - etwa Da Vincis Mona Lisa und Botticellis Venus in der Malerei oder das Kolosseum und das Pantheon in der Architektur. Im vorliegenden Beitr...

We present a novel method for detecting communities in bipartite networks. Based on an extension of the $k$-clique community detection algorithm, we demonstrate how modular structure in bipartite networks presents itself as overlapping bicliques. If bipartite information is available, the bi-clique community detection algorithm retains all of the a...

Are some ways of measuring scientific quality better than others? We analyze the reliability and precision of commonly-used methods for ranking scientific citation records. We demonstrate that the inaccuracy of several widely-used measures of quality renders them unsuitable for practical use.

We study community structure of networks. We have developed a scheme for maximizing the modularity Q [Newman and Girvan, Phys. Rev. E 69, 026113 (2004)] based on mean field methods. Further, we have defined a simple family of random networks with community structure; we understand the behavior of these networks analytically. Using these networks, w...

Are some ways of measuring scientific quality better than others? Sune Lehmann, Andrew D. Jackson and Benny E. Lautrup analyse the reliability of commonly used methods for comparing citation records.

We present a general Bayesian method for quantifying the statistical reliability of one-dimensional measures of scientific quality based on citation data. Two quality measures used in practice -- ``papers per year'' and ``Hirsch's $h$'' -- are shown to lack the accuracy and precision necessary to be useful. The mean, median and maximum number of ci...

In this paper, we explore the consequences of a distinction between ‘live' and ‘dead' network nodes; ‘live' nodes are able to acquire new links whereas ‘dead' nodes are static. We develop an analytically soluble growing network model incorporating this distinction and show that it can provide a quantitative description of the empirical network comp...

Scientific communities are characterized by strong stratification. The highly skewed frequency distribution of citations of published scientific papers suggests a relatively small number of active, cited papers embedded in a sea of inactive and uncited papers. We propose an analytically soluble model which allows for the death of nodes. This model...

The citation network constituted by the SPIRES database is investigated empirically. The probability that a given paper in the SPIRES database has k citations is well described by simple power laws, P(k) proportional to k(-alpha), with alpha approximately 1.2 for k less than 50 citations and alpha approximately 2.3 for 50 or more citations. A consi...

Im vorliegenden Aufsatz kartieren wir komplexe Netzwerkeigenschaften der Archäologischen Bibliographie. Insbesondere beleuchten wir die allgemeine Struktur thematischer Unterteilungen sowie die(Ko-)Popularität spezifischer Themen in Publikationen der Klassischen Archäologie – entsprechend den Aufzeichnungen der bibliographischen Datenbank seit 1956...