Online Popularity and Topical Interests through the Lens of Instagram

Online socio-technical systems can be studied as proxy of the real world to investigate human behavior and social interactions at scale. Here we focus on Instagram, a media-sharing online platform whose popularity has been rising up to gathering hundred millions users. Instagram exhibits a mixture of features including social structure, social tagging and media sharing. The network of social interactions among users models various dynamics including follower/followee relations and users' communication by means of posts/comments. Users can upload and tag media such as photos and pictures, and they can "like" and comment each piece of information on the platform. In this work we investigate three major aspects on our Instagram dataset: (i) the structural characteristics of its network of heterogeneous interactions, to unveil the emergence of self organization and topically-induced community structure; (ii) the dynamics of content production and consumption, to understand how global trends and popular users emerge; (iii) the behavior of users labeling media with tags, to determine how they devote their attention and to explore the variety of their topical interests. Our analysis provides clues to understand human behavior dynamics on socio-technical systems, specifically users and content popularity, the mechanisms of users' interactions in online environments and how collective trends emerge from individuals' topical interests.Comment: 11 pages, 11 figures, Proceedings of ACM Hypertext 201

A lightweight, graph-theoretic model of class-based similarity to support object-oriented code reuse.

The work presented in this thesis is principally concerned with the development of a method and set of tools designed to support the identification of class-based similarity in collections of object-oriented code. Attention is focused on enhancing the potential for software reuse in situations where a reuse process is either absent or informal, and the characteristics of the organisation are unsuitable, or resources unavailable, to promote and sustain a systematic approach to reuse. The approach builds on the definition of a formal, attributed, relational model that captures the inherent structure of class-based, object-oriented code. Based on code-level analysis, it relies solely on the structural characteristics of the code and the peculiarly object-oriented features of the class as an organising principle: classes, those entities comprising a class, and the intra and inter-class relationships existing between them, are significant factors in defining a two-phase similarity measure as a basis for the comparison process. Established graph-theoretic techniques are adapted and applied via this model to the problem of determining similarity between classes. This thesis illustrates a successful transfer of techniques from the domains of molecular chemistry and computer vision. Both domains provide an existing template for the analysis and comparison of structures as graphs. The inspiration for representing classes as attributed relational graphs, and the application of graph-theoretic techniques and algorithms to their comparison, arose out of a well-founded intuition that a common basis in graph-theory was sufficient to enable a reasonable transfer of these techniques to the problem of determining similarity in object-oriented code. The practical application of this work relates to the identification and indexing of instances of recurring, class-based, common structure present in established and evolving collections of object-oriented code. A classification so generated additionally provides a framework for class-based matching over an existing code-base, both from the perspective of newly introduced classes, and search "templates" provided by those incomplete, iteratively constructed and refined classes associated with current and on-going development. The tools and techniques developed here provide support for enabling and improving shared awareness of reuse opportunity, based on analysing structural similarity in past and ongoing development, tools and techniques that can in turn be seen as part of a process of domain analysis, capable of stimulating the evolution of a systematic reuse ethic

Improving analytics in urban water management: a spectral clustering-based approach for leakage localization

Worldwide growing water demand has been forcing utilities to successfully manage their costs. Contemporarily, within an era of tight budgets in most economic and social sectors, it affects also Water Distribution Networks (WDN). So, an efficient urban water management is needed to get a balance between consumer satisfaction and infrastructural assets inherent to WDN. Particular case is referred to pipe networks which suffer for frequent leaks, failures and service disruptions. The ensuing costs due to inspection, repair and replacement, are a significant part of operational expenses and give rise to difficult decision making. Recently, the goal regarding the improvement of the traditional leakage management process through the development of analytical leakage localization tools has been brought to the forefront leading to the proposal of several approaches. The basis of all methods relies on the fact that leaks can be detected correlating changes in flow to the output of a simulation model whose parameters are related to both location and severity of the leak. This paper, starting from a previous work of the authors, shows how the critical phases of leak localization can be accomplished through a combination of hydraulic simulation and clustering. The research deals with the benefits provided by Spectral Clustering which is usually adopted for network analysis tasks (e.g., community or sub-network discovery). A transformation from a data points dataset, consisting of leakage scenarios simulated through a hydraulic simulation model, to a similarity graph is presented. Spectral Clustering is then applied on the similarity graph and results are compared with those provided by traditional clustering techniques on the original data points dataset. The proposed spectral approach proved to be more effective with respect to traditional clustering, having a better performance to analytically localize leaks in a water distribution network and, consequently, reducing costs for intervention, inspection and rehabilitation.Peer ReviewedPostprint (published version

Label monitoring on document streams

Magdeburg, Univ., Fak. für Informatik, Diss., 2012von René Schul

Froth across the Universe Dynamics and Stochastic Geometry of the Cosmic Foam

A review on the properties and dynamical origin and nature of the cosmic foam, the tenuous space-filling frothy network permeating the interior of the Universe. We discuss the properties of this striking and intriguing pattern, describing its observational appearance, and seeking to elucidate its dynamical origin and nature. An extensive discussion on the gravitational formation and dynamical evolution of weblike patterns puts particular emphasis on the formative role of the generic anisotropy of the cosmic gravitational force fields. These tidal fields play an essential role in shaping the pattern of the large scale cosmic matter distribution. Special attention is put on a geometrical and stochastic framework for a systematic evaluation of its fossil information content on the cosmic structure formation process. Its distinct geometric character and the stochastic nature provides the cosmic web with some unique and at first unexpected properties. The implications for galaxy clustering are discussed on the basis of its relevant branch of mathematics, stochastic geometry. Central within this context are Voronoi tessellations, which have been found to represent a surprisingly versatile model for spatial cellular distributions.Comment: Invited review, Proceedings 2nd Hellenic Cosmology Workshop, eds. M. Plionis, S. Cotsakis, I. Georgantopoulos, Kluwer, 153 pages, 56 figures. Full resolution version available at http://www.astro.rug.nl/~weygaert/tim1publication/weyhellas2001.ps.g