851 resultados para reti power law social network analysis sna borsa italiana misure di centralità e potere scale free


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In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

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L’industria musicale non ha mai vissuto un periodo di cambiamento così intenso e profondo come al giorno d’oggi. La sua digitalizzazione attraverso lo streaming musicale, la nascita di nuovi dispositivi che ne consentano la fruizione e l’interazione tra industria discografica e un pubblico sempre più centrale e determinante nelle scelte produttive e distributive del mercato, sono solo alcuni degli aspetti, indubbiamente i più importanti, che caratterizzano questa nuova fase della storia della musica. Attraverso questa tesi di laurea ho cercato di osservare e approfondire come in questi ultimi anni l’industria musicale si stia approcciando al mondo dei social network per promuovere e distribuire i prodotti musicali. Viene tracciato un quadro generale dell’ambiente dei social media, mostrandone sia i lati tecnologici che sociali, fino ad evidenziarne aspetti positivi e negativi. Nella seconda parte della trattazione invece, vengono osservate le strategie comunicative adottate dagli artisti e dagli addetti ai lavori per arrivare più efficacemente al pubblico e il ruolo che rivestono i vecchi media e l’utenza nel diffondere su larga scala il prodotto musicale.

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Different types of water bodies, including lakes, streams, and coastal marine waters, are often susceptible to fecal contamination from a range of point and nonpoint sources, and have been evaluated using fecal indicator microorganisms. The most commonly used fecal indicator is Escherichia coli, but traditional cultivation methods do not allow discrimination of the source of pollution. The use of triplex PCR offers an approach that is fast and inexpensive, and here enabled the identification of phylogroups. The phylogenetic distribution of E. coli subgroups isolated from water samples revealed higher frequencies of subgroups A1 and B23 in rivers impacted by human pollution sources, while subgroups D1 and D2 were associated with pristine sites, and subgroup B1 with domesticated animal sources, suggesting their use as a first screening for pollution source identification. A simple classification is also proposed based on phylogenetic subgroup distribution using the w-clique metric, enabling differentiation of polluted and unpolluted sites.

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The research reported here draws on a study of five teenagers from a Dinka-speaking community of Sudanese settling in Australia. A range of factors including language proficiency, social network structure and language attitudes are examined as possible causes for the variability of language use. The results and discussion illustrate how the use of a triangular research approach captured the complexity of the participants' language situation and was critical to developing a full understanding of the interplay of factors influencing the teens' language maintenance and shift in a way that no single method could. Further, it shows that employment of different methodologies allowed for flexibility in data collection to ensure the fullest response from participants. Overall, this research suggests that for studies of non-standard communities, variability in research methods may prove more of a strength that the use of standardised instruments and approaches.

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Epidemiological studies of drug misusers have until recently relied on two main forms of sampling: probability and convenience. The former has been used when the aim was simply to estimate the prevalence of the condition and the latter when in depth studies of the characteristics, profiles and behaviour of drug users were required, but each method has its limitations. Probability samples become impracticable when the prevalence of the condition is very low, less than 0.5% for example, or when the condition being studied is a clandestine activity such as illicit drug use. When stratified random samples are used, it may be difficult to obtain a truly representative sample, depending on the quality of the information used to develop the stratification strategy. The main limitation of studies using convenience samples is that the results cannot be generalised to the whole population of drug users due to selection bias and a lack of information concerning the sampling frame. New methods have been developed which aim to overcome some of these difficulties, for example, social network analysis, snowball sampling, capture-recapture techniques, privileged access interviewer method and contact tracing. All these methods have been applied to the study of drug misuse. The various methods are described and examples of their use given, drawn from both the Brazilian and international drug misuse literature.

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A investigação desenvolvida no âmbito do projeto Estratégias de Intervenção socioeducativa em contextos sociais complexos enquadra-se na avaliação das políticas sociais e educativas, em particular no que diz respeito à segurança escolar em contextos marcados pela diversidade e complexidade social e cultural. O processo de avaliação centrou-se na análise das estratégias de intervenção socioeducativa relativas ao problema da violência na escola, desenvolvidas em três escolas de um concelho da Área Metropolitana de Lisboa. Partindo do pressuposto que a violência na escola é um fenómeno multideterminado e multifacetado, a pesquisa centrou-se numa abordagem que enquadra as esferas de intervenção/ação das instituições formais e dos agentes sociais enquanto mecanismos que estruturam e regulam as concepções e práticas de violência na escola. A recolha e sistematização de informação centrou-se, por um lado, nas estratégias de intervenção que têm vindo a ser desenvolvidas localmente pelas escolas, e, por outro, nas perspetivas dos diferentes intervenientes, considerando-se os alunos, osprofessores, as direções escolares e representantes das entidades e instituições locais. Metodologicamente, privilegiou-se o cruzamento de métodos de carácter extensivo e intensivo, combinando técnicas como a Observação Direta, a realização de Entrevistas, de Grupos Focais, de Questionários, e ainda, a Análise de Redes e a Análise Documental. Numa fase posterior, os diversos intervenientes participaram na discussão e análise dos resultados previamente recolhidos, e na validação conjunta de uma metodologia de intervenção que define um conjunto de estratégias gerais de combate às situações de violência na escola e nos territórios educativos. Esta metodologia é o principal produto do projeto e resulta de um processo de avaliação dinâmico e participado. A contribuição que se apresenta no VI Encontro do CIED ocupa-se dos procedimentos de avaliação desenvolvidos no âmbito deste projeto.

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Spatial analysis and social network analysis typically take into consideration social processes in specific contexts of geographical or network space. The research in political science increasingly strives to model heterogeneity and spatial dependence. To better understand and geographically model the relationship between “non-political” events, streaming data from social networks, and political climate was the primary objective of the current study. Geographic information systems (GIS) are useful tools in the organization and analysis of streaming data from social networks. In this study, geographical and statistical analysis were combined in order to define the temporal and spatial nature of the data eminating from the popular social network Twitter during the 2014 FIFA World Cup. The study spans the entire globe because Twitter’s geotagging function, the fundamental data that makes this study possible, is not limited to a geographic area. By examining the public reactions to an inherenlty non-political event, this study serves to illuminate broader questions about social behavior and spatial dependence. From a practical perspective, the analyses demonstrate how the discussion of political topics fluсtuate according to football matches. Tableau and Rapidminer, in addition to a set basic statistical methods, were applied to find patterns in the social behavior in space and time in different geographic regions. It was found some insight into the relationship between an ostensibly non-political event – the World Cup - and public opinion transmitted by social media. The methodology could serve as a prototype for future studies and guide policy makers in governmental and non-governmental organizations in gauging the public opinion in certain geographic locations.

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Introduction Collaboration is one of the defining features of contemporary scientific research, and it is particularly important with regard to neglected diseases that primarily affect developing countries. Methods The present study has identified publications on leishmaniasis in the Medline database from 1945 to 2010, analyzing them according to bibliometric indicators and statistics from social network analysis. Examining aspects such as scientific production, diachronic evolution, and collaboration and configuration of the research groups in the field, we have considered the different types of Leishmania studied and the institutional affiliation and nationality of the authors. Results Seven-hundred and thirty-five authors participate in 154 prominent research clusters or groups. Although the most predominant and consolidated collaborations are characterized by members from the same country studying the same type of Leishmania, there are also notable links between authors from different countries or who study different clinical strains of the disease. Brazil took the lead in this research, with numerous Brazilian researchers heading different clusters in the center of the collaboration network. Investigators from the USA, India, and European countries, such as France, Spain, the United Kingdom, and Italy, also stand out within the network. Conclusions Research should be fostered in countries such as Bangladesh, Nepal, Sudan, and Ethiopia, where there is a high prevalence of different forms of the disease but limited research development with reference authors integrated into the collaboration networks.

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This work presents research conducted to understand the role of indicators in decisions of technology innovation. A gap was detected in the literature of innovation and technology assessment about the use and influence of indicators in this type of decision. It was important to address this gap because indicators are often frequent elements of innovation and technology assessment studies. The research was designed to determine the extent of the use and influence of indicators in decisions of technology innovation, to characterize the role of indicators in these decisions, and to understand how indicators are used in these decisions. The latter involved the test of four possible explanatory factors: the type and phase of decision, and the context and process of construction of evidence. Furthermore, it focused on three Portuguese innovation groups: public researchers, business R&D&I leaders and policymakers. The research used a combination of methods to collect quantitative and qualitative information, such as surveys, case studies and social network analysis. This research concluded that the use of indicators is different from their influence in decisions of technology innovation. In fact, there is a high use of indicators in these decisions, but lower and differentiated differences in their influence in each innovation group. This suggests that political-behavioural methods are also involved in the decisions to different degrees. The main social influences in the decisions came mostly from hierarchies, knowledge-based contacts and users. Furthermore, the research established that indicators played mostly symbolic roles in decisions of policymakers and business R&D&I leaders, although their role with researchers was more differentiated. Indicators were also described as helpful instruments to conduct a reasonable interpretation of data and to balance options in innovation and technology assessments studies, in particular when contextualised, described in detail and with discussion upon the options made. Results suggest that there are four main explanatory factors for the role of indicators in these decisions: First, the type of decision appears to be a factor to consider when explaining the role of indicators. In fact, each type of decision had different influences on the way indicators are used, and each type of decision used different types of indicators. Results for policy-making were particularly different from decisions of acquisition and development of products/technology. Second, the phase of the decision can help to understand the role indicators play in these decisions. Results distinguished between two phases detected in all decisions – before and after the decision – as well as two other phases that can be used to complement the decision process and where indicators can be involved. Third, the context of decision is an important factor to consider when explaining the way indicators are taken into consideration in policy decisions. In fact, the role of indicators can be influenced by the particular context of the decision maker, in which all types of evidence can be selected or downplayed. More importantly, the use of persuasive analytical evidence appears to be related with the dispute existent in the policy context. Fourth and last, the process of construction of evidence is a factor to consider when explaining the way indicators are involved in these decisions. In fact, indicators and other evidence were brought to the decision processes according to their availability and capacity to support the different arguments and interests of the actors and stakeholders. In one case, an indicator lost much persuasion strength with the controversies that it went through during the decision process. Therefore, it can be argued that the use of indicators is high but not very influential; their role is mostly symbolic to policymakers and business decisions, but varies among researchers. The role of indicators in these decisions depends on the type and phase of the decision and the context and process of construction of evidence. The latter two are related to the particular context of each decision maker, the existence of elements of dispute and controversies that influence the way indicators are introduced in the decision-making process.

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The work reported in this thesis addresses the research question of when and how positive psychological states impact positive behavior and positive organizational development. We present two theoretical essays and three empirical studies to find possible answers to this question and we use a multitude of methodologies with different epistemological assumptions, including quantitative correlation analysis, social network analysis and qualitative grounded theory analysis. In the whole, our work shows that positive psychological states are fundamental to promote individual and organizational higher-levels of performance and well-being. It also points that the capability to induce positive psychological states in others (an “alter-positive” approach) is a powerful way to develop outstanding individuals and organizations. In a broader sense, it stresses the need to promote good vibrations as a fundamental route to create a better world.

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Independent regulatory agencies (IRAs) were created in various sectors and on different governmental levels to implement liberalization policies. This paper investigates the link between IRAs' independence, which is said to promote regulatory credibility and the use of technical expertise, and their accountability, which is related to the need for controlling and legitimizing independent regulators. The literature on the regulatory state anticipates a positive relation between the independence and accountability of IRAs, but systematic empirical evidence is still lacking. To tackle this question, this paper measures and compares the independence and the accountability of IRAs in three differentially liberalized sectors in Switzerland (telecommunications, electricity and railways). With the application of Social Network Analysis, this piece of research shows that IRAs can be de facto independent and accountable at the same time, but the two features do not necessarily co-evolve in the same direction.

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A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together narratology, both close and distant reading approaches, and social network analysis. It is in line with recent attempts to automatise the extraction of literary social networks (Elson, 2012; Sack, 2013) and other studies stressing the importance of character- systems (Woloch, 2003; Moretti, 2011). The method we use to build the network is direct and simple. First, we extract co-occurrences from a book index, without the need for text analysis. We then describe the narrative roles of the characters, which we deduce from their respective positions in the network, i.e. the discourse. As a case study, we use the autobiographical novel Les Confessions by Jean-Jacques Rousseau. We start by identifying co-occurrences of characters in the book index of our edition (Slatkine, 2012). Subsequently, we compute four types of centrality: degree, closeness, betweenness, eigenvector. We then use these measures to propose a typology of narrative roles for the characters. We show that the two parts of Les Confessions, written years apart, are structured around mirroring central figures that bear similar centrality scores. The first part revolves around the mentor of Rousseau; a figure of openness. The second part centres on a group of schemers, depicting a period of deep paranoia. We also highlight characters with intermediary roles: they provide narrative links between the societies in the life of the author. The method we detail in this complete case study of character network analysis can be applied to any work documented by an index. Un réseau de personnages modélise les relations entre les personnages d'un récit : les relations sont basées sur une forme de proximité dans le texte, l'apparition commune dans des événements, des citations dans des dialogues, etc. Notre travail propose un cadre théorique pour l'analyse des réseaux de personnages, rassemblant narratologie, close et distant reading, et analyse des réseaux sociaux. Ce travail prolonge les tentatives récentes d'automatisation de l'extraction de réseaux sociaux tirés de la littérature (Elson, 2012; Sack, 2013), ainsi que les études portant sur l'importance des systèmes de personnages (Woloch, 2003; Moretti, 2011). La méthode que nous utilisons pour construire le réseau est directe et simple. Nous extrayons les co-occurrences d'un index sans avoir recours à l'analyse textuelle. Nous décrivons les rôles narratifs des personnages en les déduisant de leurs positions relatives dans le réseau, donc du discours. Comme étude de cas, nous avons choisi le roman autobiographique Les Confessions, de Jean- Jacques Rousseau. Nous déduisons les co-occurrences entre personnages de l'index présent dans l'édition Slatkine (Rousseau et al., 2012). Sur le réseau obtenu, nous calculons quatre types de centralité : le degré, la proximité, l'intermédiarité et la centralité par vecteur propre. Nous utilisons ces mesures pour proposer une typologie des rôles narratifs des personnages. Nous montrons que les deux parties des Confessions, écrites à deux époques différentes, sont structurées autour de deux figures centrales, qui obtiennent des mesures de centralité similaires. La première partie est construite autour du mentor de Rousseau, qui a symbolisé une grande ouverture. La seconde partie se focalise sur un groupe de comploteurs, et retrace une période marquée par la paranoïa chez l'auteur. Nous mettons également en évidence des personnages jouant des rôles intermédiaires, et de fait procurant un lien narratif entre les différentes sociétés couvrant la vie de l'auteur. La méthode d'analyse des réseaux de personnages que nous décrivons peut être appliquée à tout texte de fiction comportant un index.

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The objective of the thesis was to explore the nature and characteristics of customer-related internal communication in a global industrial matrix organization during a specific customer relationship, and how it could be improved. The theoretical part of the study views the field of the concepts of intra-organizational information and knowledge sharing. The theoretical part also views the internal communications influences to customer relationships, its problematic, and the suggestions to improve internal communication in literature. The empirical part of the study was conducted with the Content Analysis and the Social Network Analysis as research methods. The data was collected by interviews and a questionnaire. Internal communication was observed first generally within the organization from the point of view of a certain business, and secondly, during a specific customer relationship at personal level and at departmental level. The results of the study describe the nature and characteristics of internal communication in the organization. The results give 13 suggestions for improving internal communication in the organization. Although the study has been done in one specific organization, it also offers insights for other organizations as well as managers to improve their internal communication.