Google matrix analysis of Wikipedia networks

Cette thèse s’intéresse à l’analyse du réseau dirigé extrait de la structure des hyperliens deWikipédia. Notre objectif est de mesurer les interactions liant un sous-ensemble de pages duréseau Wikipédia. Par conséquent, nous proposons de tirer parti d’une nouvelle représentationmatricielle appelée matrice réduite de Google ou "reduced Google Matrix". Cette matrice réduitede Google (GR) est définie pour un sous-ensemble de pages donné (c-à-d un réseau réduit).Comme pour la matrice de Google standard, un composant de GR capture la probabilité que deuxnoeuds du réseau réduit soient directement connectés dans le réseau complet. Une desparticularités de GR est l’existence d’un autre composant qui explique la probabilité d’avoir deuxnoeuds indirectement connectés à travers tous les chemins possibles du réseau entier. Dans cettethèse, les résultats de notre étude de cas nous montrent que GR offre une représentation fiabledes liens directs et indirects (cachés). Nous montrons que l’analyse de GR est complémentaire àl’analyse de "PageRank" et peut être exploitée pour étudier l’influence d’une variation de lien surle reste de la structure du réseau. Les études de cas sont basées sur des réseaux Wikipédiaprovenant de différentes éditions linguistiques. Les interactions entre plusieurs groupes d’intérêtont été étudiées en détail : peintres, pays et groupes terroristes. Pour chaque étude, un réseauréduit a été construit. Les interactions directes et indirectes ont été analysées et confrontées à desfaits historiques, géopolitiques ou scientifiques. Une analyse de sensibilité est réalisée afin decomprendre l’influence des liens dans chaque groupe sur d’autres noeuds (ex : les pays dansnotre cas). Notre analyse montre qu’il est possible d’extraire des interactions précieuses entre lespeintres, les pays et les groupes terroristes. On retrouve par exemple, dans le réseau de peintresissu de GR, un regroupement des artistes par grand mouvement de l’histoire de la peinture. Lesinteractions bien connues entre les grands pays de l’UE ou dans le monde entier sont égalementsoulignées/mentionnées dans nos résultats. De même, le réseau de groupes terroristes présentedes liens pertinents en ligne avec leur idéologie ou leurs relations historiques ou géopolitiques.Nous concluons cette étude en montrant que l’analyse réduite de la matrice de Google est unenouvelle méthode d’analyse puissante pour les grands réseaux dirigés. Nous affirmons que cetteapproche pourra aussi bien s’appliquer à des données représentées sous la forme de graphesdynamiques. Cette approche offre de nouvelles possibilités permettant une analyse efficace desinteractions d’un groupe de noeuds enfoui dans un grand réseau dirig

Cyber-herding and cyber activism countering Qutbists on the internet

The Internet provides Islamic militants ("Qutbists") a golden opportunity to bypass normal media outlets and take their message directly to the people. This allows them to spread their ideas to an ever-growing audience. What should be done about these web sites has been the focus of an ongoing debate. Some advocate shutting down these web sites while others prefer to monitor them for information. Both views have merit, and both have problems. The purpose of this thesis is to propose and evaluate three strategies for countering Qutbists on the internet: a covert active strategy of cyber-herding, an overt passive strategy of cyber activism, and a combination of these two strategies.http://archive.org/details/cyberherdingndcy109453092US Air Force (USAF) author.Approved for public release; distribution is unlimited

clicktatorship and democrazy: Social media and political campaigning

This chapter aims to direct attention to the political dimension of the social media age. Although current events like the Cambridge Analytica data breach managed to raise awareness for the issue, the systematically organized and orchestrated mechanisms at play still remain oblivious to most. Next to dangerous monopoly-tendencies among the powerful players on the market, reliance on automated algorithms in dealing with content seems to enable large-scale manipulation that is applied for economical and political purposes alike. The successful replacement of traditional parties by movements based on personality cults around marketable young faces like Emmanuel Macron or Austria’s Sebastian Kurz is strongly linked to products and services offered by an industry that simply provides likes and followers for cash. Inspired by Trump’s monopolization of the Twitter-channel, these new political acteurs use the potential of social media for effective message control, allowing them to avoid confrontations with professional journalists. In addition, an extremely active minority of organized agitators relies on the viral potential of the web to strongly influence and dictate public discourse – suggesting a shift from the Spiral of Silence to the dangerous illusion of a Nexus of Noise

Visual Affect Around the World: A Large-scale Multilingual Visual Sentiment Ontology

Every culture and language is unique. Our work expressly focuses on the uniqueness of culture and language in relation to human affect, specifically sentiment and emotion semantics, and how they manifest in social multimedia. We develop sets of sentiment- and emotion-polarized visual concepts by adapting semantic structures called adjective-noun pairs, originally introduced by Borth et al. (2013), but in a multilingual context. We propose a new language-dependent method for automatic discovery of these adjective-noun constructs. We show how this pipeline can be applied on a social multimedia platform for the creation of a large-scale multilingual visual sentiment concept ontology (MVSO). Unlike the flat structure in Borth et al. (2013), our unified ontology is organized hierarchically by multilingual clusters of visually detectable nouns and subclusters of emotionally biased versions of these nouns. In addition, we present an image-based prediction task to show how generalizable language-specific models are in a multilingual context. A new, publicly available dataset of >15.6K sentiment-biased visual concepts across 12 languages with language-specific detector banks, >7.36M images and their metadata is also released.Comment: 11 pages, to appear at ACM MM'1

Macroeconomic forecasting with statistically validated knowledge graphs

This study leverages narrative from global newspapers to construct theme-based knowledge graphs about world events, demonstrating that features extracted from such graphs improve forecasts of industrial production in three large economies compared to a number of benchmarks. Our analysis relies on a filtering methodology that extracts “backbones” of statistically significant edges from large graph data sets. We find that changes in the eigenvector centrality of nodes in such backbones capture shifts in relative importance between different themes significantly better than graph similarity measures. We supplement our results with an interpretability analysis, showing that the theme categories “disease” and “economic” have the strongest predictive power during the time period that we consider. Our work serves as a blueprint for the construction of parsimonious – yet informative – theme-based knowledge graphs to monitor in real time the evolution of relevant phenomena in socio-economic systems

Controversy trend detection in social media

In this research, we focus on the early prediction of whether topics are likely to generate significant controversy (in the form of social media such as comments, blogs, etc.). Controversy trend detection is important to companies, governments, national security agencies, and marketing groups because it can be used to identify which issues the public is having problems with and develop strategies to remedy them. For example, companies can monitor their press release to find out how the public is reacting and to decide if any additional public relations action is required, social media moderators can moderate discussions if the discussions start becoming abusive and getting out of control, and governmental agencies can monitor their public policies and make adjustments to the policies to address any public concerns. An algorithm was developed to predict controversy trends by taking into account sentiment expressed in comments, burstiness of comments, and controversy score. To train and test the algorithm, an annotated corpus was developed consisting of 728 news articles and over 500,000 comments on these articles made by viewers from CNN.com. This study achieved an average F-score of 71.3% across all time spans in detection of controversial versus non-controversial topics. The results suggest that it is possible for early prediction of controversy trends leveraging social media

Bootstrapping Web Archive Collections From Micro-Collections in Social Media

In a Web plagued by disappearing resources, Web archive collections provide a valuable means of preserving Web resources important to the study of past events. These archived collections start with seed URIs (Uniform Resource Identifiers) hand-selected by curators. Curators produce high quality seeds by removing non-relevant URIs and adding URIs from credible and authoritative sources, but this ability comes at a cost: it is time consuming to collect these seeds. The result of this is a shortage of curators, a lack of Web archive collections for various important news events, and a need for an automatic system for generating seeds. We investigate the problem of generating seed URIs automatically, and explore the state of the art in collection building and seed selection. Attempts toward generating seeds automatically have mostly relied on scraping Web or social media Search Engine Result Pages (SERPs). In this work, we introduce a novel source for generating seeds from URIs in the threaded conversations of social media posts created by single or multiple users. Users on social media sites routinely create and share narratives about news events consisting of hand-selected URIs of news stories, tweets, videos, etc. In this work, we call these posts Micro-collections, whether shared on Reddit or Twitter, and we consider them as an important source for seeds. This is because, the effort taken to create Micro-collections is an indication of editorial activity and a demonstration of domain expertise. Therefore, we propose a model for generating seeds from Micro-collections. We begin by introducing a simple vocabulary, called post class for describing social media posts across different platforms, and extract seeds from the Micro-collections post class. We further propose Quality Proxies for seeds by extending the idea of collection comparison to evaluation, and present our Micro-collection/Quality Proxy (MCQP) framework for bootstrapping Web archive collections from Micro-collections in social media

Performing Legality in the Theatre of Hostilities: Asymmetric Conflict, Lawfare and the Rise of Vicarious Litigation

This Article explores the extent of the change by looking at the ways in which asymmetric conflict and legalization have reshaped the theatre of hostilities and the implications for the institution of war itself. The shift from one literal battlefield to multiple and disaggregated battlespaces has led to a reconfigured theatre of hostilities, which now involves a complex mix of local and global spaces as well as kinetic and narrative forms of combat. This re-making of armed hostilities in geographical, material, and social terms has increased access to the drama, stage, and audience of military theatres. Further, the more globalized and publicized character of hostilities has allowed a higher number of actors, and actors of higher quality, to participate in and observe hostilities, whether kinetic, narrative, or both. This has given a powerful platform for law to mediate the conduct of warfare, and it is thus unsurprising that the notion of legality regularly occupies center stage in a reconstructed theatre of hostilities. Accordingly, military actors, whether state or non-state, are producing performances of legality in combat to influence not only their adversaries but also, crucially, formal and informal judgments across the theatre’s more expansive and global audience. The term “performances” does not imply cynical theatrics, but rather concerted actions to display legality or illegality as an integral part of warfare. In this way, such performances of legality have become a crucial strategic asset for interacting kinetic and narrative confrontations. This has led to a distinctive struggle between adversaries over appearances of legality and illegality, which has produced an institutional and narrative battlespace of growing importance that this Article conceptualizes as vicarious litigation. The Article is organized in five sections. Section I introduces and elaborates on the related notions of legal performances and vicarious litigation by bridging sociological theorizing on social performances with noted developments in asymmetric warfare. This conceptual effort draws insight from Performative Sociology and the so-called “practice turn” in international relations theory. Section II describes the origin of vicarious litigation as flowing from the asymmetric warfare’s disruption of the institutional bargain behind modern war and, consequently, International Humanitarian Law (IHL). To understand that institutional disruption, Section II discusses Andrew Mack’s under-examined inquiry into and conceptualization of “asymmetric conflict.” Sections III and IV look at how international lawyers, and specifically IHL scholars, have struggled to grasp the rise of asymmetric conflict and how the dominant “lawfare” literature has suffered from conceptual straining and the incapacity to theorize institutional change precipitated by the prevalence of asymmetric conflict. Section V focuses on the novel notions of legal performances and vicarious litigation and examines how these novel notions provide alternatives to the hobbled semantics of lawfare by offering greater insight into institutional mutations that now define the legalization of contemporary warfare