Event detection on streams of short texts for decision-making

L'objectif de cette thèse est de concevoir d'évènements sur les réseaux sociaux permettant d'assister les personnes en charge de prises de décisions dans des contextes industriels. Le but est de créer un système de détection d'évènement permettant de détecter des évènements à la fois ciblés, propres à des domaines particuliers mais aussi des évènements généraux. En particulier, nous nous intéressons à l'application de ce système aux chaînes d'approvisionnements et plus particulièrement celles liées aux matières premières. Le défi est de mettre en place un tel système de détection, mais aussi de déterminer quels sont les évènements potentiellement impactant dans ces contextes. Cette synthèse résume les différentes étapes des recherches menées pour répondre à ces problématiques. Architecture d'un système de détection d'évènements Dans un premier temps, nous introduisons les différents éléments nécessaires à la constitution d'un système de détection d'évènements. Ces systèmes sont classiquement constitués d'une étape de filtrage et de nettoyage des données, permettant de s'assurer de la qualité des données traitées par le reste du système. Ensuite, ces données sont représentées de manière à pouvoir être regroupées par similarité. Une fois ces regroupements de données établis, ils sont analysés de manière à savoir si les documents les constituants traitent d'un évènement ou non. Finalement, l'évolution dans le temps de ces évènements est suivie. Nous avons proposé au cours de cette thèse d'étudier les problématiques propres à chacune de ces étapes. Représentation textuelles de documents issus des réseaux sociaux Nous avons comparé différentes méthodes de représentations des données textuelles, dans le contexte de notre système de détection d'évènements. Nous avons comparé les performances de notre système de détection à l'algorithme First Story Detection (FSD), un algorithme ayant les mêmes objectifs. Nous avons d'abord démontré que le système que nous proposons est plus performant que le FSD, mais aussi que les architectures récentes de réseaux de neurones (transformeur) sont plus performantes que TF-IDF dans notre contexte, contrairement à ce qui avait été montré dans le contexte du FSD. Nous avons ensuite proposé de combiner différentes représentations textuelles afin d'exploiter conjointement leurs forces. Détection d'évènement, suivi et évaluation Nous avons proposé des approches pour les composantes d'analyse de regroupement de documents ainsi que pour le suivi de l'évolution de ces évènements. En particulier, nous utilisons l'entropie et la diversité d'utilisateurs introduits dans [Rajouter les citations] pour évaluer les regroupements. Nous suivons ensuite leur évolution au cours du temps en faisant des comparaisons entre regroupements à des instants différents, afin de créer des chaînes de regroupements. Enfin, nous avons étudié comment évaluer des systèmes de détection d'évènements dans des contextes où seulement peu de données annotées par des humains sont disponibles. Nous avons proposé une méthode permettant d'évaluer automatiquement les systèmes de détection d'évènement en exploitant des données partiellement annotées. Application au contexte des matières premières. Afin de spécifier les types d'évènements à superviser, nous avons mené une étude historique des évènements ayant impacté le cours des matières premières. En particulier, nous nous sommes focalisé sur le phosphate, une matière première stratégique. Nous avons étudié les différents facteurs ayant une influence, proposé une méthode reproductible pouvant être appliquée à d'autres matières premières ou d'autres domaines. Enfin, nous avons dressé une liste d'éléments à superviser pour permettre aux experts d'anticiper les variations des cours.The objective of this thesis is to design an event detection system on social networks to assist people in charge of decision-making in industrial contexts. The event detection system must be able to detect both targeted, domain-specific events and general events. In particular, we are interested in the application of this system to supply chains and more specifically those related to raw materials. The challenge is to build such a detection system, but also to determine which events are potentially influencing the raw materials supply chains. This synthesis summarizes the different stages of research conducted to answer these problems. Architecture of an event detection system First, we introduce the different building blocks of an event detection system. These systems are classically composed of a data filtering and cleaning step, ensuring the quality of the data processed by the system. Then, these data are embedded in such a way that they can be clustered by similarity. Once these data clusters are created, they are analyzed in order to know if the documents constituting them discuss an event or not. Finally, the evolution of these events is tracked. In this thesis, we have proposed to study the problems specific to each of these steps. Textual representation of documents from social networks We compared different text representation models, in the context of our event detection system. We also compared the performances of our event detection system to the First Story Detection (FSD) algorithm, an algorithm with the same objectives. We first demonstrated that our proposed system performs better than FSD, but also that recent neural network architectures perform better than TF-IDF in our context, contrary to what was shown in the context of FSD. We then proposed to combine different textual representations in order to jointly exploit their strengths. Event detection, monitoring, and evaluation We have proposed different approaches for event detection and event tracking. In particular, we use the entropy and user diversity introduced in ... to evaluate the clusters. We then track their evolution over time by making comparisons between clusters at different times, in order to create chains of clusters. Finally, we studied how to evaluate event detection systems in contexts where only few human-annotated data are available. We proposed a method to automatically evaluate event detection systems by exploiting partially annotated data. Application to the commodities context In order to specify the types of events to supervise, we conducted a historical study of events that have impacted the price of raw materials. In particular, we focused on phosphate, a strategic raw material. We studied the different factors having an influence, proposed a reproducible method that can be applied to other raw materials or other fields. Finally, we drew up a list of elements to supervise to enable experts to anticipate price variations

Self-adaptive multi-agent systems for aided decision-making : an application to maritime surveillance

L'activité maritime s'est fortement développée ces dernières années et sert de support à de nombreuses activités illicites. Il est devenu nécessaire que les organismes impliqués dans la surveillance maritime disposent de systèmes efficaces pour les aider à identifier ces activités illicites. Les Systèmes de Surveillance Maritime doivent observer de manière efficace un espace maritime large, à identifier des anomalies de comportement des navires évoluant dans l'espace en question, et à déclencher des alertes documentées si ces anomalies amènent à penser que les navires ont un comportement suspect. Nous proposons un modèle générique de système multi-agents, que nous appelons MAS4AT, capable de remplir deux des différents rôles d'un système de surveillance : la représentation numérique des comportements des entités surveillées et des mécanismes d'apprentissage pour une meilleure efficacité. MAS4AT est intégré au système I2C.The maritime activity has widely grow in the last few years and is the witness of several illegal activities. It has become necessary that the organizations involved in the maritime surveillance possess efficient systems to help them in their identification. The maritime surveillance systems must observe a wide maritime area, identify the anomalies in the behaviours of the monitored ships et trigger alerts when these anomalies leads to a suspicious behavior. We propose a generic agent model, called MAS4AT, able to fulfil two main roles of a surveillance system: the numerical representation of the behaviours of the monitored entities and learning mechanisms for a better efficiency. MAS4AT is integrated in the system I2C

Europe in the Age of Post-Truth Politics

This open access book is the product of three years of academic research that has been carried out in the EU-funded Jean Monnet Network on “Post-Truth Politics, Nationalism and the Delegitimation of European Integration” since 2019. Drawing on the multidisciplinary expertise of the network’s members, the book explores the impact of the phenomenon of post-truth politics on European integration and the European Union. It places particular emphasis on how post-truth politics has played out in the public sphere and asks what impact the phenomenon has had on public deliberation, but reflects also on its implications for democracy in a wider sense. This book is primarily written for audiences with an interest in politics and policy making, including academics, policy makers and civil-society actors. Thanks to its accessible style, the book should however also be an asset to wider audiences

Europe in the Age of Post-Truth Politics

This open access book is the product of three years of academic research that has been carried out in the EU-funded Jean Monnet Network on “Post-Truth Politics, Nationalism and the Delegitimation of European Integration” since 2019. Drawing on the multidisciplinary expertise of the network’s members, the book explores the impact of the phenomenon of post-truth politics on European integration and the European Union. It places particular emphasis on how post-truth politics has played out in the public sphere and asks what impact the phenomenon has had on public deliberation, but reflects also on its implications for democracy in a wider sense. This book is primarily written for audiences with an interest in politics and policy making, including academics, policy makers and civil-society actors. Thanks to its accessible style, the book should however also be an asset to wider audiences

Towards an understanding of ICT in the Hamad Health Science Library in the State of Qatar

Information and communication technologies (lCTs) are increasingly changing the way in which working, learning, doing research and administrations are carried out. ICTs have the changed natute of many academic, public and organisations libraries. Health service is an important and essential element of any modern society. Therefore, development of this service and updating its services is a priority for most of modern governments. Current developments in ICTs are changing the nature of health science libraries. Therefore research in this area is important to provide guidelines, recommendations to improve the health services. This study explores the impact of ICTs in Hamad Health Science Library in Qatar. Physicians and staff in the Hamad Medical Corporation were surveyed by questionnaire to identify the use of ICTs and their effect on them. Then personal interviews detertnined their perceptions of the impact on the research productivity of end-users. There is a lack of this type of study in the literature. Those that there are specifically address the impact of ICTs in health science library. ICTs have become a major link to health care resources for many health care workers. The study employs a systems methodological approach in order to better understand the impact and value of ICTs in Hamad Health Sciences Library (HHSL). Using the systems intervention, issues that affect the system were identified (technological issues, cooperation issues, cultural issues and staff (and user) training and development) and the problem situation improved. An ordered roadmap of elements necessary to bring about change was produced and a HHSL systems model constructed to understand the change processes in context. Conclusions drawn reflect the level of success of the aims and objectives and indicate ways in which the problem situation can be improved from a systemic standpoint. Recommendations to management include aspects associated with operational planning, policy objectives and strategic formulation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Politics of the Heart and Mind : Using WhatsApp to Drive Support Amongst Evangelicals in Brazil

Dissertation (MA (Political Sciences))--University of Pretoria, 2022.On the 28 October 2018, Brazilians elected right-wing populist Jair Messias Bolsonaro as the 38th President of Brazil. Bolsonaro defeated his opponent Fernando Haddad from the PT, by a significant margin of 55,13% as against 43,87% (Araujuo & Prior 2020). Even against the backdrop of surging support for right-wing candidates and parties, the election of Bolsonaro still surprised observers and academics. Bolsonaro’s success, as Leticia Cesarino (2019) and Stuart Davis and Joe Straubhaar (2020) found, was due to his campaign’s communication strategy on social media. At the heart of these strategies is the use of emotive messaging on WhatsApp, which micro-targeted Evangelicals through the use of fake news, particularly disinformation, and populist communication derived from crises occurring in Brazil leading up to the 2018 election. Grounded in these arguments, this dissertation studies the effects of fear, anger and enthusiasm/hope in communication shared by the Bolsonaro campaign on WhatsApp. In doing so, the study applies a two-step analysis method. Firstly, the 12 sample WhatsApp messages were analysed using a latent content analysis to identify and explore the topics addressed in these messages. Secondly, these messages were then subjected to an emotional sentiment analysis to measure their emotive elements using the Linguistic-Inquiry and Word Count software. Guided by the Theory of Affective Intelligence, this dissertation found that anger and enthusiasm are evoked by WhatsApp messaging based on political habits, while fear is evoked by messaging grounded in an unknown threat. Moreover, anger and enthusiasm are found to decrease information-seeking, while fear encourages individuals to seek alternative information. The Bolsonaro WhatsApp network acted as both an echo-chamber for individuals experiencing anger/enthusiasm, and an alternative source of information for individuals experiencing fear. This dissertation shows how the Bolsonaro campaign used emotive strategic communication on WhatsApp to appeal to Evangelical Christians, specifically their desire for social recognition.Political SciencesMA (Political Sciences)Unrestricte