Detecting Political Framing Shifts and the Adversarial Phrases within\\ Rival Factions and Ranking Temporal Snapshot Contents in Social Media

abstract: Social Computing is an area of computer science concerned with dynamics of communities and cultures, created through computer-mediated social interaction. Various social media platforms, such as social network services and microblogging, enable users to come together and create social movements expressing their opinions on diverse sets of issues, events, complaints, grievances, and goals. Methods for monitoring and summarizing these types of sociopolitical trends, its leaders and followers, messages, and dynamics are needed. In this dissertation, a framework comprising of community and content-based computational methods is presented to provide insights for multilingual and noisy political social media content. First, a model is developed to predict the emergence of viral hashtag breakouts, using network features. Next, another model is developed to detect and compare individual and organizational accounts, by using a set of domain and language-independent features. The third model exposes contentious issues, driving reactionary dynamics between opposing camps. The fourth model develops community detection and visualization methods to reveal underlying dynamics and key messages that drive dynamics. The final model presents a use case methodology for detecting and monitoring foreign influence, wherein a state actor and news media under its control attempt to shift public opinion by framing information to support multiple adversarial narratives that facilitate their goals. In each case, a discussion of novel aspects and contributions of the models is presented, as well as quantitative and qualitative evaluations. An analysis of multiple conflict situations will be conducted, covering areas in the UK, Bangladesh, Libya and the Ukraine where adversarial framing lead to polarization, declines in social cohesion, social unrest, and even civil wars (e.g., Libya and the Ukraine).Dissertation/ThesisDoctoral Dissertation Computer Science 201

Three essays on the use of neural networks for financial prediction

The number of studies trying to explain the causes and consequences of the economic and financial crises usually rises considerably after a banking crisis occurs. The dramatic effects of the most recent financial crisis on the real economy around the world call for a better comprehension of previous crises as a way to anticipate future crisis episodes. It is precisely this objective, preventing future crises, the main motivation of this PhD dissertation. We identify two important mechanisms that have failed during the latest years and that are closely related to the onset of the financial crisis: The assessment of the solvency of banks along with the systemic risk over the time, and the detection of the macroeconomic imbalances in some countries, especially in Europe, which made the financial crisis evolve through a sovereign crisis. Our dissertation is made up of three different essays, trying to go a step ahead in the knowledge of these mechanisms.Departamento de Economía Financiera y ContabilidadDoctorado en Economía de la Empres

Sustainable Smart Cities and Smart Villages Research

ca. 200 words; this text will present the book in all promotional forms (e.g. flyers). Please describe the book in straightforward and consumer-friendly terms. [There is ever more research on smart cities and new interdisciplinary approaches proposed on the study of smart cities. At the same time, problems pertinent to communities inhabiting rural areas are being addressed, as part of discussions in contigious fields of research, be it environmental studies, sociology, or agriculture. Even if rural areas and countryside communities have previously been a subject of concern for robust policy frameworks, such as the European Union’s Cohesion Policy and Common Agricultural Policy Arguably, the concept of ‘the village’ has been largely absent in the debate. As a result, when advances in sophisticated information and communication technology (ICT) led to the emergence of a rich body of research on smart cities, the application and usability of ICT in the context of a village has remained underdiscussed in the literature. Against this backdrop, this volume delivers on four objectives. It delineates the conceptual boundaries of the concept of ‘smart village’. It highlights in which ways ‘smart village’ is distinct from ‘smart city’. It examines in which ways smart cities research can enrich smart villages research. It sheds light on the smart village research agenda as it unfolds in European and global contexts.

A methodology to produce geographical information for land planning using very-high resolution images

Actualmente, os municípios são obrigados a produzir, no âmbito da elaboração dos instrumentos de gestão territorial, cartografia homologada pela autoridade nacional. O Plano Director Municipal (PDM) tem um período de vigência de 10 anos. Porém, no que diz respeito à cartografia para estes planos, principalmente em municípios onde a pressão urbanística é elevada, esta periodicidade não é compatível com a dinâmica de alteração de uso do solo. Emerge assim, a necessidade de um processo de produção mais eficaz, que permita a obtenção de uma nova cartografia de base e temática mais frequentemente. Em Portugal recorre-se à fotografia aérea como informação de base para a produção de cartografia de grande escala. Por um lado, embora este suporte de informação resulte em mapas bastante rigorosos e detalhados, a sua produção têm custos muito elevados e consomem muito tempo. As imagens de satélite de muito alta-resolução espacial podem constituir uma alternativa, mas sem substituir as fotografias aéreas na produção de cartografia temática, a grande escala. O tema da tese trata assim da satisfação das necessidades municipais em informação geográfica actualizada. Para melhor conhecer o valor e utilidade desta informação, realizou-se um inquérito aos municípios Portugueses. Este passo foi essencial para avaliar a pertinência e a utilidade da introdução de imagens de satélite de muito alta-resolução espacial na cadeia de procedimentos de actualização de alguns temas, quer na cartografia de base quer na cartografia temática. A abordagem proposta para solução do problema identificado baseia-se no uso de imagens de satélite e outros dados digitais em ambiente de Sistemas de Informação Geográfica. A experimentação teve como objectivo a extracção automática de elementos de interesse municipal a partir de imagens de muito alta-resolução espacial (fotografias aéreas ortorectificadas, imagem QuickBird, e imagem IKONOS), bem como de dados altimétricos (dados LiDAR). Avaliaram-se as potencialidades da informação geográfica extraídas das imagens para fins cartográficos e analíticos. Desenvolveram-se quatro casos de estudo que reflectem diferentes usos para os dados geográficos a nível municipal, e que traduzem aplicações com exigências diferentes. No primeiro caso de estudo, propõe-se uma metodologia para actualização periódica de cartografia a grande escala, que faz uso de fotografias aéreas vi ortorectificadas na área da Alta de Lisboa. Esta é uma aplicação quantitativa onde as qualidades posicionais e geométricas dos elementos extraídos são mais exigentes. No segundo caso de estudo, criou-se um sistema de alarme para áreas potencialmente alteradas, com recurso a uma imagem QuickBird e dados LiDAR, no Bairro da Madre de Deus, com objectivo de auxiliar a actualização de cartografia de grande escala. No terceiro caso de estudo avaliou-se o potencial solar de topos de edifícios nas Avenidas Novas, com recurso a dados LiDAR. No quarto caso de estudo, propõe-se uma série de indicadores municipais de monitorização territorial, obtidos pelo processamento de uma imagem IKONOS que cobre toda a área do concelho de Lisboa. Esta é uma aplicação com fins analíticos onde a qualidade temática da extracção é mais relevante.Currently, the Portuguese municipalities are required to produce homologated cartography, under the Territorial Management Instruments framework. The Municipal Master Plan (PDM) has to be revised every 10 years, as well as the topographic and thematic maps that describe the municipal territory. However, this period is inadequate for representing counties where urban pressure is high, and where the changes in the land use are very dynamic. Consequently, emerges the need for a more efficient mapping process, allowing obtaining recent geographic information more often. Several countries, including Portugal, continue to use aerial photography for large-scale mapping. Although this data enables highly accurate maps, its acquisition and visual interpretation are very costly and time consuming. Very-High Resolution (VHR) satellite imagery can be an alternative data source, without replacing the aerial images, for producing large-scale thematic cartography. The focus of the thesis is the demand for updated geographic information in the land planning process. To better understand the value and usefulness of this information, a survey of all Portuguese municipalities was carried out. This step was essential for assessing the relevance and usefulness of the introduction of VHR satellite imagery in the chain of procedures for updating land information. The proposed methodology is based on the use of VHR satellite imagery, and other digital data, in a Geographic Information Systems (GIS) environment. Different algorithms for feature extraction that take into account the variation in texture, color and shape of objects in the image, were tested. The trials aimed for automatic extraction of features of municipal interest, based on aerial and satellite high-resolution (orthophotos, QuickBird and IKONOS imagery) as well as elevation data (altimetric information and LiDAR data). To evaluate the potential of geographic information extracted from VHR images, two areas of application were identified: mapping and analytical purposes. Four case studies that reflect different uses of geographic data at the municipal level, with different accuracy requirements, were considered. The first case study presents a methodology for periodic updating of large-scale maps based on orthophotos, in the area of Alta de Lisboa. This is a situation where the positional and geometric accuracy of the extracted information are more demanding, since technical mapping standards must be complied. In the second case study, an alarm system that indicates the location of potential changes in building areas, using a QuickBird image and LiDAR data, was developed for the area of Bairro da Madre de Deus. The goal of the system is to assist the updating of large scale mapping, providing a layer that can be used by the municipal technicians as the basis for manual editing. In the third case study, the analysis of the most suitable roof-tops for installing solar systems, using LiDAR data, was performed in the area of Avenidas Novas. A set of urban environment indicators obtained from VHR imagery is presented. The concept is demonstrated for the entire city of Lisbon, through IKONOS imagery processing. In this analytical application, the positional quality issue of extraction is less relevant.GEOSAT – Methodologies to extract large scale GEOgraphical information from very high resolution SATellite images (PTDC/GEO/64826/2006), e-GEO – Centro de Estudos de Geografia e Planeamento Regional, da Faculdade de Ciências Sociais e Humanas, no quadro do Grupo de Investigação Modelação Geográfica, Cidades e Ordenamento do Territóri

Fuzzy Techniques for Decision Making 2018

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Machine Learning Methods with Noisy, Incomplete or Small Datasets

In many machine learning applications, available datasets are sometimes incomplete, noisy or affected by artifacts. In supervised scenarios, it could happen that label information has low quality, which might include unbalanced training sets, noisy labels and other problems. Moreover, in practice, it is very common that available data samples are not enough to derive useful supervised or unsupervised classifiers. All these issues are commonly referred to as the low-quality data problem. This book collects novel contributions on machine learning methods for low-quality datasets, to contribute to the dissemination of new ideas to solve this challenging problem, and to provide clear examples of application in real scenarios

Bridging the Gap

The concept of resilience has arisen as a “new way of thinking”, becoming a response to both the causes and effects of ongoing global challenges. As it strongly stresses cities’ transformative potential, resilience’s final purpose is to prevent and manage unforeseen events and improve communities’ environmental and social quality. Although the resilience theory has been investigated in depth, several methodological challenges remain, mainly related to the concept’s practical sphere. As a matter of fact, resilience is commonly criticised for being too ambiguous and empty of meaning. At the same time, turning resilience into practice is not easy to do. This will arguably be one of the most impactful global issues for future research on resilience. The Special Issue “Bridging the Gap: The Measure of Urban Resilience” falls under this heading, and it seeks to synthesise state-of-the-art knowledge of theories and practices on measuring resilience. The Special Issue collected 11 papers that address the following questions: “What are the theoretical perspectives of measuring urban resilience? What are the existing methods for measuring urban resilience? What are the main features that a technique for measuring urban resilience needs to have? What is the role of measuring urban resilience in operationalising cities’ ability to adapt, recover and benefit from shocks?

Developing Advanced Photogrammetric Methods for Automated Rockfall Monitoring

[eng] In recent years, photogrammetric models have become a widely used tool in the field of geosciences thanks to their ability to reproduce natural surfaces. As an alternative to other systems such as LiDAR (Light Detection and Ranging), photogrammetry makes it possible to obtain 3D points clouds at a lower cost and with a lower learning curve. This combination has allowed the democratisation of this 3D model creation strategy. On the other hand, rockfalls are one of the geological phenomena that represent a risk for society. It is the most common natural phenomenon in mountainous areas and, given its great speed, its hazard is very high. This doctoral thesis deals with the creation of photogrammetric systems and processing algorithms for the automatic monitoring of rockfalls. To this end, 3 fixed camera photogrammetric systems were designed and installed in 2 study areas. In addition, 3 different workflows have been developed, two of which are aimed at obtaining comparisons of higher quality using photogrammetric models and the other focused on automating the entire monitoring process with the aim of obtaining automatic monitoring systems of low temporal frequency. The photogrammetric RasPi system has been designed and installed in the study area of Puigcercós (Catalonia). This very low-cost system has been designed using Raspberry cameras. Despite being a very low-cost and low-resolution system, the results obtained demonstrate its ability to identify rockfalls and pre-failure deformation. The HRCam photogrammetric system has also been designed and installed in the Puigcercós study area. This system uses commercial cameras and more complex control systems. With this system, higher quality models have been obtained that enable better monitoring of rockfalls. Finally, the DSLR system has been designed similarly to the HRCam system but has been installed in a real risk area in the Tajo de San Pedro in the Alhambra (Andalusia). This system has been used to constantly monitor the rockfalls affecting this escarpment. In order to obtain 3D comparisons with the highest possible quality, two workflows have been developed. The first, called PCStacking, consists of stacking 3D models in order to calculate the median of the Z coordinates of each point to generate a new averaged point cloud. This thesis shows the application of the algorithm both with ad hoc created synthetic point clouds and with real point clouds. In both cases, the 25th and 75th percentile errors of the 3D comparisons were reduced from 3.2 cm to 1.4 cm in synthetic tests and from 1.5 cm to 0.5 cm in real conditions. The second workflow that has been developed is called MEMI (Multi-Epoch and Multi-Imagery). This workflow is capable of obtaining photogrammetric comparisons with a higher quality than those obtained with the classical workflow. The redundant use of images from the two periods to be compared reduces the error to a factor of 2 compared to the classical approach, yielding a standard deviation of the comparison of 3D models of 1.5 cm. Finally, the last workflow presented in this thesis is an update and an automation of the method for detecting rockfalls from point-clouds carried out by the RISKNAT research group. The update has been carried out with two objectives in mind. The first is to transfer the entire working method to free licence (both language and programming), and the second is to include in the processing the new algorithms and improvements that have recently been developed. The automation of the method has been performed to cope with the large amount of data generated by photogrammetric systems. It consists of automating all the processes, which means that everything from the capture of the image in the field to the obtention of the rockfalls is performed automatically. This automation poses important challenges, which, although not completely solved, are addressed in this thesis. Thanks to the creation of photogrammetric systems, 3D model improvement algorithms and automation of the rockfall identification workflow, this doctoral thesis presents a solid and innovative proposal in the field of low-cost automatic monitoring. The creation of these systems and algorithms constitutes a further step in the unimpeded expansion of monitoring and warning systems, whose ultimate goal is to enable us to live in a safer world and to build more resilient societies to deal with geological hazards.[cat] En els darrers anys, els models fotogramètrics s’han convertit en una eina molt utilitzada en l’àmbit de les geociències gràcies a la seva capacitat per reproduir superfícies naturals. Com a alternativa a altres sistemes com el LiDAR (Light Detection and Ranging), la fotogrametria permet obtenir núvols de punts 3D a un cost més baix i amb una corba d’aprenentatge menor. Per altra banda, els despreniments de roca són un dels fenòmens geològics que representen un risc per al conjunt de la societat. Aquesta tesi doctoral aborda la creació de sistemes fotogramètrics i algoritmes de processat per al monitoratge automàtic de despreniments de roca. Per una banda, s’ha dissenyat un sistema fotogramètric de molt baix cost fent servir càmeres Raspberry Pi, anomenat RasPi System, instal·lat a la zona d’estudi de Puigcercós (Catalunya). Per altra banda, s’ha dissenyat un sistema fotogramètric d’alta resolució anomenat HRCam també instal·lat a la zona d’estudi de Puigcercós. Finalment, s’ha dissenyat un tercer sistema fotogramètric de manera similar al sistema HRCam anomenat DSLR, instal·lat en una zona de risc real al Tajo de San Pedro de l’Alhambra (Andalusia). Per obtenir comparacions 3D amb la màxima qualitat possible, s’han desenvolupat dos fluxos de treball. El primer, anomenat PCStacking consisteix a realitzar un apilament de models 3D per tal de calcular la mediana de les coordenades Z de cada punt. El segon flux de treball que s’ha desenvolupat s’anomena MEMI (Multi-Epoch and Multi-Imagery). Aquest flux de treball és capaç d’obtenir comparacions fotogramètriques amb una qualitat superior a les que s’obtenen amb el flux de treball clàssic. Finalment, el darrer flux de treball que es presenta en aquesta tesi és una actualització i una automatització del mètode de detecció de despreniments de roca del grup de recerca RISKNAT. L’actualització s’ha dut a terme perseguint dos objectius. El primer, traspassar tot el mètode de treball a llicència lliure (tant llenguatge com programari) i el segon, incloure els nous algoritmes i millores desenvolupats en aquesta tesi en el processat fotogramètric Gràcies a la creació dels sistemes fotogramètrics, algoritmes de millora de models 3D i l’automatització en la identificació de despreniments aquesta tesi doctoral presenta una proposta sòlida i innovadora en el camp del monitoratge automàtic de baix cost. La creació d’aquests sistemes i algoritmes representen un avenç important en l’expansió dels sistemes de monitoratge i alerta que tenen com a objectiu final permetre'ns viure en un món més segur i construir societats més resilients enfront dels riscos geològics

Footfall and the territorialisation of urban places measured through the rhythms of social activity

The UK high street is constantly changing and evolving in response to, for example, online sales, out-of-town developments, and economic crises. With over 10 years of hourly footfall counts from sensors across the UK, this study was an opportunity to perform a longitudinal and quantitative investigation to diagnose how these changes are reflected in the changing patterns of pedestrian activity. Footfall provides a recognised performance measure of place vitality. However, through a lack of data availability due to historic manual counting methods, few opportunities to contextualise the temporal patterns longitudinally have existed. This study therefore investigates daily, weekly, and annual footfall patterns, to diagnose the similarities and differences between places as social activity patterns from UK high streets evolve over time. Theoretically, footfall is conceptualised within the framework of Territorology and Assemblage Theory, conceptually underpinning a quantitative approach to represent the collective meso-level (street and town-centre) patterns of footfall (social) activity. To explore the data, the periodic signatures of daily, weekly, and annual footfall are extracted using STL (seasonal trend decomposition using Loess) algorithms and the outputs are then analysed using fuzzy clustering techniques. The analyses successfully identify daily, weekly, and annual periodic patterns and diagnose the varying social activity patterns for different urban place types and how places, both individually and collectively are changing. Footfall is demonstrated to be a performance measure of meso-scale changes in collective social activity. For place management, the fuzzy analysis provides an analytical tool to monitor the annual, weekly, and daily footfall signatures providing an evidence-based diagnostic of how places are changing over time. The place manager is therefore better able to identify place specific interventions that correspond to the usage patterns of visitors and adapt these interventions as behaviours change