Social media censorship in times of political unrest: a social simulation experiment with the UK riots

Following the 2011 wave of political unrest, extending from the Arab Spring to the UK riots, the formation of a large consensus around Internet censorship is underway. The present paper adopts a social simulation approach to show that the decision to “regulate”, filter or censor social media in situations of unrest changes the pattern of civil protest and ultimately results in higher levels of violence. Building on Epstein's (2002) agent-based model, several alternative scenarios are generated. The systemic optimum, represented by complete absence of censorship, not only corresponds to lower levels of violence over time, but allows for significant periods of social peace after each outburst

Visualization in mixed-methods research on social networks

Introduction to edited special section of Sociological Research Onlin

An ethno-computational approach to friendship in SNS

This paper focuses on how different configurations of privacy settings, content-sharing and culture traits display affect the formation of online friendship networks. By adopting an innovative ethno-computational methodology (as developed in Tubaro & Casilli, 2010), we draw on a participant observation carried out on the popular SNS Facebook to subsequently inform an agent-based model. The ethnographic phase suggests the hypothesis that culture traits display plays a crucial role in the creation of ties and is motivated by social capital maximisation. This hypothesis is problematized through the analysis of simulated network data. New dynamics emerge from the computational interaction of agents, such as 1) a tension between bridging and bonding dynamics; 2) relevance of privacy settings; 3) anomie. As homophily alone fails to account for tie formation and maintenance, Lahire’s (2004) notion of “cultural dissonance” – through which individuals adhere to their group culture while preserving their “self distinction” – can be productively conjured up to explain friendship formation in online social networks

Efficient Geometry-Based Sound Reverberation

Publication in the conference proceedings of EUSIPCO, Toulouse, France, 200

Selection of Sampling Grid and Prefilter for Image Decimation Based on Spectral Extension Analysis

Signal decimation aimed at optimal spectral packing has a variety of applications in areas ranging from array pro cessing to image processing In this article we propose and discuss a new method for determining decimation grid and prelter that best t the spectral extension of any D signal dened on an arbitrary sampling lattice The method has been implemented and tested on digital images in order to evaluate quality degradation due to optimal spectral truncatio

Légitimation intersubjective de la présence en ligne et formation de réseaux sociaux: Une approche ethno-computationnelle

Cette étude porte sur le rôle de la légitimation des descriptions physiques et culturelles (apparence, goûts, styles, préférences) dans les interactions assistées par ordinateur au sein d‟un site généraliste de networking social. En employant une méthodologie mixte empirique et computationnelle, un modèle multi-agents est construit à partir d‟une observation participante menée dans le réseau Facebook. Les résultats préliminaires montrent comment différentes configurations de trois éléments (présentation de soi, options de protection de la vie privée et partage de contenus) affectent inégalement les modalités de légitimation réciproque de la présence et – finalement – concourent à la formation de réseaux d‟« amitié » en ligne aux configurations multiples. En analysant les caractéristiques structurelles (densité, centralité, homophilie, etc.) ainsi que les dynamiques de construction de relations sociales entre bridging et bonding, des stratégies sociales visant à trouver un équilibre entre adhésion aux valeurs du groupe et « dissonance culturelle » font surface

Two-dimensional beam tracing from visibility diagrams for real-time acoustic rendering

We present an extension of the fast beam-tracing method presented in the work of Antonacci et al. (2008) for the simulation of acoustic propagation in reverberant environments that accounts for diffraction and diffusion. More specifically, we show how visibility maps are suitable for modeling propagation phenomena more complex than specular reflections. We also show how the beam-tree lookup for path tracing can be entirely performed on visibility maps as well. We then contextualize such method to the two different cases of channel (point-to-point) rendering using a headset, and the rendering of a wave field based on arrays of speakers. Finally, we provide some experimental results and comparisons with real data to show the effectiveness and the accuracy of the approach in simulating the soundfield in an environment

Searching for dominant high-level features for music information retrieval

Music Information Retrieval systems are often based on the analysis of a large number of low-level audio features. When dealing with problems of musical genre description and visualization, however, it would be desirable to work with a very limited number of highly informative and discriminant macro-descriptors. In this paper we focus on a specific class of training-based descriptors, which are obtained as the loglikelihood of a Gaussian Mixture Model trained with short musical excerpts that selectively exhibit a certain semantic homogeneity. As these descriptors are critically dependent on the training sets, we approach the problem of how to automatically generate suitable training sets and optimize the associated macro-features in terms of discriminant power and informative impact. We then show the application of a set of three identified macro-features to genre visualization, tracking and classification

Motion estimation and signaling techniques for 2D+t scalable video coding

We describe a fully scalable wavelet-based 2D+t (in-band) video coding architecture. We propose new coding tools specifically designed for this framework aimed at two goals: reduce the computational complexity at the encoder without sacrificing compression; improve the coding efficiency, especially at low bitrates. To this end, we focus our attention on motion estimation and motion vector encoding. We propose a fast motion estimation algorithm that works in the wavelet domain and exploits the geometrical properties of the wavelet subbands. We show that the computational complexity grows linearly with the size of the search window, yet approaching the performance of a full search strategy. We extend the proposed motion estimation algorithm to work with blocks of variable sizes, in order to better capture local motion characteristics, thus improving in terms of rate-distortion behavior. Given this motion field representation, we propose a motion vector coding algorithm that allows to adaptively scale the motion bit budget according to the target bitrate, improving the coding efficiency at low bitrates. Finally, we show how to optimally scale the motion field when the sequence is decoded at reduced spatial resolution. Experimental results illustrate the advantages of each individual coding tool presented in this paper. Based on these simulations, we define the best configuration of coding parameters and we compare the proposed codec with MC-EZBC, a widely used reference codec implementing the t+2D framework

Extraction of acoustic sources for multiple arrays based on the ray space transform

In this paper we present a source extraction technique for multiple uniform linear arrays distributed in space. The technique adopts the Ray Space Transform representation of the sound field, which is inherently based on the Plane Wave Decomposition. The Ray Space Transform gives us an intuitive representation of the acoustic field, thus enabling the adoption of geometrically-motivated constraints in the spatial filter design. The proposed approach is semi-blind since it needs as input an estimate of the source positions. We prove the effectiveness of the proposed solution through simulations using both white noise and speech signals