Camille Roth

Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows

The spatial arrangement of urban hubs and centers and how individuals interact with these centers is a crucial problem with many applications ranging from urban planning to epidemiology. We utilize here in an unprecedented manner the large scale, real-time ‘Oyster’ card database of individual person movements in the London subway to reveal the structure and organization of the city. We show that patterns of intraurban movement are strongly heterogeneous in terms of volume, but not in terms of distance travelled, and that there is a polycentric structure composed of large flows organized around a limited number of activity centers. For smaller flows, the pattern of connections becomes richer and more complex and is not strictly hierarchical since it mixes different levels consisting of different orders of magnitude. This new understanding can shed light on the impact of new urban projects on the evolution of the polycentric configuration of a city and the dense structure of its centers and it provides an initial approach to modeling flows in an urban system.

Social and semantic coevolution in knowledge networks

Abstract Socio-semantic networks involve agents creating and processing information: communities of scientists, software developers, wiki contributors and webloggers are, among others, examples of such knowledge networks. We aim at demonstrating that the dynamics of these communities can be adequately described as the coevolution of a social and a socio-semantic network. More precisely, we will first introduce a theoretical framework based on a social network and a socio-semantic network, i.e. an epistemic network featuring agents, concepts and links between agents and between agents and concepts. Adopting a relevant empirical protocol, we will then describe the joint dynamics of social and socio-semantic structures, at both macroscopic and microscopic scales, emphasizing the remarkable stability of these macroscopic properties in spite of a vivid local, agent-based network dynamics.

Reducing the Representation Complexity of Lattice-Based Taxonomies

Representing concept lattices constructed from large contexts often results in heavy, complex diagrams that can be impractical to handle and, eventually, to make sense of. In this respect, many concepts could allegedly be dropped from the lattice without impairing its relevance towards a taxonomy description task at a certain level of detail. We propose a method where the notion of stability is introduced to select potentially more pertinent concepts. We present some theoretical properties of stability and discuss several use cases where taxonomy building is an issue.

Towards concise representation for taxonomies of epistemic communities

We present an application of formal concept analysis aimed at representing a meaningful structure of knowledge communities in the form of a lattice-based taxonomy. The taxonomy groups together agents (community members) who interact and/or develop a set of notions--i.e. cognitive properties of group members. In the absence of appropriate constraints on how it is built, a knowledge community taxonomy is in danger of becoming extremely complex, and thus difficult to comprehend. We consider two approaches to building a concise representation that respects the underlying structural relationships, while hiding uninteresting and/or superfluous information. The first is a pruning strategy that is based on the notion of concept stability, and the second is a representational improvement based on nested line diagrams. We illustrate the method with a small sample of a community of embryologists.

Approaches to the selection of relevant concepts in the case of noisy data

Concept lattices built on noisy data tend to be large and hence hard to interpret. We introduce several measures that can be used in selecting relevant concepts and discuss how they can be combined together. We study their performance in a series of experiments.

A long-time limit for world subway networks

We study the temporal evolution of the structure of the worlds largest subway networks in an exploratory manner. We show that, remarkably, all these networks converge to a shape that shares similar generic features despite their geographical and economic differences. This limiting shape is made of a core with branches radiating from it. For most of these networks, the average degree of a node (station) within the core has a value of order 2.5 and the proportion of k = 2 nodes in the core is larger than 60 per cent. The number of branches scales roughly as the square root of the number of stations, the current proportion of branches represents about half of the total number of stations, and the average diameter of branches is about twice the average radial extension of the core. Spatial measures such as the number of stations at a given distance to the barycentre display a first regime which grows as r2 followed by another regime with different exponents, and eventually saturates. These results—difficult to interpret in the framework of fractal geometry—confirm and yield a natural explanation in the geometric picture of this core and their branches: the first regime corresponds to a uniform core, while the second regime is controlled by the interstation spacing on branches. The apparent convergence towards a unique network shape in the temporal limit suggests the existence of dominant, universal mechanisms governing the evolution of these structures.

Academic team formation as evolving hypergraphs

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions.

Socio-semantic Dynamics in a Blog Network

The blogosphere can be construed as a knowledge network made of bloggers who are interacting through a social network to share, exchange or produce information. We claim that the social and semantic dimensions are essentially co-determined and propose to investigate the co-evolutionary dynamics of the blogosphere by examining two intertwined issues: first, how does knowledge distribution drive new interactions and thus influence the social network topology? Second, which role structural network properties play in the information circulation in the system?We adopt an empirical standpoint by analyzing the semantic and social activity of a portion of the US political blogosphere, monitored on a period of four months.

Epistemic communities: description and hierarchic categorization

ABSTRACT Understanding the structure of knowledge communities, and particularly the organization of “epistemic communities”, or groups of agents sharing common knowledge concerns, is usually based on either social relationships or semantic similarity. To link social and semantic aspects, a formal framework based on Galois lattices (or concept lattices) categorizes epistemic communities in an automated and hierarchically structured way. The process rebuilds a whole community structure and taxonomy, and notably fields and subfields gathering a certain proportion of agents. It is applied to empirical data to exhibit these alleged structural properties, successfully compared with categories given by domain experts.

Viable wikis: struggle for life in the wikisphere

Wikis are collaborative platforms enabling collective elaboration of knowledge, the most famous and possibly the most successful thereof being the Wikipedia. There are currently plenty of other active open-access wikis, with varying success: some recruit many users and achieve sustainability, while others strive to attract sufficient active contributors, irrespective of the topic of the wiki. We make an exploratory investigation of some factors likely to account for these various destinies (such as distinct policies, norms, user incentives, technical and structural features), examining the demographics of a portion of the wikisphere. We underline the intertwining of population and content dynamics and emphasize the existence of different periods of development of a wiki-based community, from bootstrapping by founders with a pre-established set of rules, to more stable regimes where constant enrollment and training of new users balances out the occasional departure of more advanced users.