Os rankings musicais destinam-se principalmente a fins de marketing, mas também ajudam os usuários a descobrir novas músicas, bem como a comparar artistas, álbuns, etc. Este trabalho apresenta uma ferramenta interativa para visualizar, encontrar e comparar rankings musicais usando diferentes técnicas além de exibir atributos das músicas. A técnica foi concebida após uma pesquisa remota que coletou dados sobre como as pessoas escolhem música. As técnicas de visualização tornam mais fácil obter informações sobre artistas e faixas, e também comparar os dados obtidos a partir dos dois principais rankings de música, Billboard e Spotify. A ferrament também permite a interação com dados pessoais. Resultados de experimentos conduzidos com usuários potenciais mostraram que a ferramenta foi considerada interessante, com um layout atrativo. Comparando com as formas tradicionais de visualizar rankings de músicas, usuários preferiram a ferramenta aqui desenvolvida, mas a diferença para Billboard e Spotify não foi grande. Entretanto, quando avaliada a usabilidade da ferramenta, os resultados foram melhores, principalmente no que se refere à filtragem e às técnicas de comparação. MusicVis foi também considerado fácil de aprender. / Music rankings are mainly aimed at marketing purposes but also help users in discovering new music as well as comparing songs, artists, albums, etc. This work presents an interactive way to visualize, find and compare music rankings using different techniques, including the display of music attributes. The technique was conceived after a remote survey we conducted to collect data about how people choose music. Our visualization makes easier to obtain information about artists and tracks, and also to compare the data gathered from the two major music rankings, namely Billboard and Spotify. The tool also provides interaction with personal data. The results obtained from experiments with potential users showed that the tool was considered interesting, with an attractive layout. Compared to traditional music ranking tools users preferred ours, but with not such a large difference from using Billboard or Spotify. However, when evaluating the usability of our tool, results are positive, mainly concerning to data filtering and comparison features. MusicVis was also considered easy to learn.

Made available in DSpace on 2018-08-01T23:40:25Z (GMT). No. of bitstreams: 1 tese_11492_Dissertação_Franciely versão final.pdf: 2283407 bytes, checksum: b1399e93e5fbf50a607a9e2b387ffb8c (MD5) Previous issue date: 2017-10-27 / CAPES / A literatura tem demostrado a forte relação entre a orientação analítica das organizações e a geração de vantagem competitiva para as mesmas (KIRON et al., 2011; KIRON; FERGUSON; PRENTICE, 2013). Nesse sentido, este estudo foi conduzido no setor supermercadista, com o intuito de compreender a forma com que a orientação analítica influencia a criação de valor – principal componente da vantagem competitiva – (BARNEY, 1991; ITO et al., 2012; PICCOLI; IVES, 2005) para os clientes. Cabe esclarecer que, para que tal objetivo fosse alcançado, foi preciso cumprir um objetivo anterior, ou seja, investigar a existência de um ranking dos atributos de valor para o cliente de supermercado, visto que não foi encontrada uma sólida discussão a esse respeito na literatura. No intuito de cumprir tais propósitos, a pesquisa adotou uma abordagem mista, sendo a primeira fase quantitativa e a segunda qualitativa. Na fase quantitativa, os dados foram coletados por meio de questionário fechado, aplicado com 480 clientes de supermercados, nas quatro principais cidades da região da Grande Vitória, isto é, Serra, Vitória, Vila Velha e Cariacica. As análises nessa fase foram feitas mediante média e teste qui-quadrado, rodados na plataforma SPSS. Já na fase qualitativa, foi empregado o estudo de caso como estratégia de pesquisa, cujos dados foram coletados por meio de entrevista semiestruturada. Nessa etapa, os dados foram analisados por meio de análise de conteúdo, com auxílio do software MAXQDA12. Os resultados da fase quantitativa apontam que existe, de fato, um ranking entre os atributos de valor para os clientes de supermercado, em que o preço, a qualidade, a variedade e a proximidade foram os atributos considerados de maior valor. Os resultados da fase qualitativa indicam que as decisões acerca de preço e qualidade – atributos de maior relevância para os clientes de supermercado – tendem a se basear em fontes de informação e processos mais analiticamente orientados. Já as decisões acerca da localização foram consideradas por esse estudo moderadamente analíticas, baseando-se em fontes de informação pouco estruturadas. Por fim, em relação à variedade, a decisão é basicamente guiada pela experiência que os tomadores de decisão têm com o negócio. Identificada a forma com que a orientação analítica influencia as decisões acerca dos atributos de valor mais relevantes para os clientes de supermercado, uma série de considerações e oportunidades são apresentadas ao final deste trabalho no sentido de se avançar com a acumulação e uso de dados, bem como com a valorização, por parte das pessoas, da informação gerada nesse processo, em detrimento da informação produzida pelo feeling. Tais oportunidades buscam explorar, além da produção e uso dos dados, a orientação analítica das pessoas, que ainda parecem confiar na experiência para gerar insights que seriam melhor suportados por processos analíticos. / The literature has demonstrated the strong relationship between the analytical orientation of organizations and the generation of competitive advantage for the same organizations (KIRON et al., 2011; KIRON, FERGUSON AND PRENTICE, 2013). Therefore, this study was conducted in the supermarket sector, in order to understand how analytical orientation influences value creation - the main component of competitive advantage - (BARNEY, 1991; ITO et al., 2012; PICCOLI; IVES , 2005) for customers. It is worth clarifying that in order to achieve this objective, it was necessary to fulfill an earlier objective, that is, to investigate the existence of a ranking of the attributes of value for the supermarket customer, since a solid discussion regarding this subject was not found in the literature. In order to fulfill these purposes, this research adopted a mixed approach, being the first a quantitative phase and the second a qualitative one. In the quantitative phase, the data was collected through a closed questionnaire, applied to 480 supermarket customers, in the four major cities of the Grande Vitória region (Serra, Vitória, Vila Velha and Cariacica). The analyses in this phase were done using averages and chi-square test, on the SPSS platform. In the qualitative phase, a case study was used as the research strategy, whose data was collected through a semistructured interview. In this stage, the data was analyzed through content analysis, using the software MAXQDA12. The results of the quantitative phase indicates that there is, in fact, a ranking among the attributes of value for supermarket customers, in which price, quality, variety and proximity were the attributes considered of the highest value. The results of the qualitative phase indicate that decisions regarding price and quality - attributes of higher relevance to supermarket customers - tend to be based on more analytically oriented sources of information and processes. Decisions regarding location were considered by this study to be moderately analytical, based on poorly structured sources of information. Finally, in relation to variety, the decision is basically guided by the experience that decision-makers have in the business area. As this research identified the way in which analytical guidance influences decisions about the most relevant value attributes for supermarket customers, a number of considerations and opportunities are presented at the end of this paper to move forward with the gathering and use of data, as well the recognition, by the people, of the information generated in this process, over the information produced by just the business feeling. Such opportunities seek to explore, beyond the generation and use of data, the analytical orientation of people, who still seems to rely on experience to generate insights that would be best supported by analytical processes.

Following the early days of the Internet and the World Wide Web, news media in Canada have gone on to develop their own news web sites with the intentions of meeting the on-line needs of media audiences, expanding their audience reach, and adding to revenue production and profitability on- and off-line. Web strategies have varied somewhat across the different media, but anecdotal evidence suggests that sports contents have been important for both print and television. This thesis focused on the latter, sports contents on television network websites, and was undertaken to evaluate how Canadian television stations are utilizing the Internet and web technologies to feature sports news and information. Only a few studies specific to sports television web sites have been done, and these have mainly focused on American news stations. The research objective of the thesis was to systematically examine the web presence of sports contents on Canadian television web sites by conducting a content analysis of identifiably unique sites in the Canadian context. A site analysis protocol was developed through an iterative process. An initial instrument was constructed drawing on past research in this area. In particular, prior work by Bates et al. (1996 & 1997), Pines (1999), Bucy, Lang, Potter & Grabe (1999), Sparks (2001) provided systematic measures for examiriirig the Web presence of television stations. Ha & James's definition of interactivity (1998) was also useful as was the work of Cho (1999), Rogers & Thorson (2000) on Internet advertising. The initial instrument was evaluated and modified during a series of trial scans. The final instrument focused on five areas: body of the home page, types of content, presentation mechanisms, interactivity and advertising. A systematic site analysis was conducted from August to October, 2003, and a total of twenty-one sports home pages were analyzed. Three web sites (TSN, Leafs TV and The Score) were found to have a good balance in the five areas evaluated in the study. The results of independent-samples t-tests showed that general television networks had more sports top news and hyperlinks to other news items than sport specialty networks. By comparison, sports specialty networks tended to have more sport-related search engines and greater efficiency of space. CBC's "Sports Forums" that were configured on its sports home page gave the public broadcaster the highest quotient for interactivity in comparison with the twenty private networks and stations in the study. Advertising was present in all of the sites, and the findings point to an increasing interest in the televisual and sport web site media in producing revenue through web-based advertising. / Education, Faculty of / Kinesiology, School of / Graduate

The purpose of this study was to determine the predictive value of selected input variables on the accountability rating of Texas high schools with student populations greater than or equal to 900. Specifically, this study analyzed the effect of student, staff and fiscal input variables in determining the odds of a high school in this study receiving a Low Performing, an Academically Acceptable, or a Recognized rating in the Texas public education accountability system - a system which is based in student performance on state standardized testing. Identifying a set of variables that helps predict campus accountability ratings provides campus administrators and teachers with information to improve student performance on standardized testing. Using statistical methods to determine the odds of campus ratings based on selected input variables, this study revealed that successful student remediation in mathematics is the most consistent, positive indicator of campus accountability rating out of 60 student, staff and fiscal inputs analyzed. However, the most telling aspect of this study is that inputs such as, teacher experience, teacher campus tenure, teacher degree level, student SAT performance, Advanced Placement testing performance and the percentage of low socioeconomic students were not statistically significant. The wider implications of these findings warrant further research into why these variables seem to have no affect on campus accountability rating.

The purpose of this study is to investigate the usefulness of statistical decomposition measures in the prediction of industrial bond rating changes. Further, the predictive ability of decomposition measures is compared with multiple discriminant analysis on the same sample. The problem of this study is twofold. It stems in general from the statistical problems associated with current techniques employed in the study of bond ratings and in particular from the lack of attention to the study of bond rating changes. Two main hypotheses are tested in this study. The first is that bond rating changes can be predicted through the use of financial statement data. The second is that decomposition analysis can achieve the same performance as multiple discriminant analysis in duplicating and predicting industrial bond rating changes. To explain and predict industrial bond rating changes, statistical decomposition measures were computed for each company in the sample. Based on these decomposition measures, the two types of analyses performed were (a) a univariate analysis where each decomposition measure was compared with an industry average decomposition measure, and (b) a multivariate analysis where decomposition measures were used as independent variables in a probability linear model. In addition to statistical decomposition analysis, multiple discriminant analysis was used in duplicating and predicting bond rating changes. Finally, a comparison was made between the predictive abilities of decomposition analysis and discriminant analysis.

Mediators of scientific knowledge are currently large scientific citation databases and platforms build upon them as they have conquered the role of the librarians in the digital environment. Direct utilization of bibliographic data for analysis of international academic mobility helps to gain insight into behavior of high impact international scholars. Geographic structure of global academia facilitates exploration of the prospect that Gravity and Radiation models can be complements to each other. In addition, author challenges role of university rankings as a principal driver of decision-making process for academic mobility.

This dissertation deals with one aspect of how city officials respond to community needs. It is about the decisions of governments on how to secure the financial resources needed to fulfill their obligations to the public. The study explores the factors that influence officials' decisions to issue debt. It is different from other municipal bond studies in that it focuses on the behavior of bond issuers rather than bond investors and the rating agencies.

The internationalization of Higher Education has caused a sweeping global shift of policies for governments and Higher Education institutions alike. This thesis aims to examine the case of China, and the three-decade evolution of internationalization as an influential norm, guiding the creation of comprehensive policies and plans through a multi-stage process. By examining the actors, motives and mechanisms behind Chinese Higher Education policies between 1990 and 2019, the impact of norm cascade and ultimate internationalization are revealed. The building and diffusion of internationalization as a norm includes the prioritization of global university rankings in addition to the increasing spotlight on research within the Higher Education sector. Constructivist theory was selected as the Theoretical Framework and employs concepts including norm-building and diffusion. This qualitative case study will examine the policies and rationales for the implementation of education initiatives as encouraged by leading actors and agents and the subsequent successes and obstacles from adoption to full implementation.

Cette thèse introduit un cadre d’analyse multirésolution pour les données de classements. Initiée au 18e siècle dans le contexte d’élections, l’analyse des données de classements a attiré un intérêt majeur dans de nombreux domaines de la littérature scientifique : psychométrie, statistiques, économie, recherche opérationnelle, apprentissage automatique ou choix social computationel entre autres. Elle a de plus été revitalisée par des applications modernes comme les systèmes de recommandation, où le but est d’inférer les préférences des utilisateurs pour leur proposer les meilleures suggestions personnalisées. Dans ces contextes, les utilisateurs expriment leurs préférences seulement sur des petits sous-ensembles d’objets variant au sein d’un large catalogue. L’analyse de tels classements incomplets pose cependant un défi important, tant du point de vue statistique que computationnel, poussant les acteurs industriels à utiliser des méthodes qui n’exploitent qu’une partie de l’information disponible. Cette thèse introduit une nouvelle représentation pour les données, qui surmonte par construction ce double défi. Bien qu’elle repose sur des résultats de combinatoire et de topologie algébrique, ses nombreuses analogies avec l’analyse multirésolution en font un cadre naturel et efficace pour l’analyse des classements incomplets. Ne faisant aucune hypothèse sur les données, elle mène déjà à des estimateurs au-delà de l’état-de-l’art pour des petits catalogues d’objets et peut être combinée avec de nombreuses procédures de régularisation pour des larges catalogues. Pour toutes ces raisons, nous croyons que cette représentation multirésolution ouvre la voie à de nombreux développements et applications futurs. / This thesis introduces a multiresolution analysis framework for ranking data. Initiated in the 18th century in the context of elections, the analysis of ranking data has attracted a major interest in many fields of the scientific literature : psychometry, statistics, economics, operations research, machine learning or computational social choice among others. It has been even more revitalized by modern applications such as recommender systems, where the goal is to infer users preferences in order to make them the best personalized suggestions. In these settings, users express their preferences only on small and varying subsets of a large catalog of items. The analysis of such incomplete rankings poses however both a great statistical and computational challenge, leading industrial actors to use methods that only exploit a fraction of available information. This thesis introduces a new representation for the data, which by construction overcomes the two aforementioned challenges. Though it relies on results from combinatorics and algebraic topology, it shares several analogies with multiresolution analysis, offering a natural and efficient framework for the analysis of incomplete rankings. As it does not involve any assumption on the data, it already leads to overperforming estimators in small-scale settings and can be combined with many regularization procedures for large-scale settings. For all those reasons, we believe that this multiresolution representation paves the way for a wide range of future developments and applications

This dissertation examines the reaction of common stock prices to changes in bond ratings by Moody's Bond Service. The question is whether an announcement of a re-rating by Moody's is new information. There are only two studies of stock price reaction to bond changes and the results are conflicting. Pinches and Singleton (1978) [PS] concluded that any reaction comes well before the re-rating. Griffin and Sanvicente (1982) [GS] found that their portfolio test indicated that rating changes do convey new information. This was particularly true for downgradings. Both studies used monthly data and neither performed a statistical testing of residual reversals. PS provided a graph of the residuals which indicated the presence of a reversal trend. GS provided no information on this topic. This study, using daily data and the cumulative prediction error technique, finds that bond re-ratings offer new information. The results indicate that the market only partially anticipates the bond change. For the downgrades, the excess return on the announcement day is .6% which is statistically significant. The residuals reverse after the announcement day, but are not statistically significant. The upgrades do not have a significant reaction on the announcement day, but have a statistically significant negative reaction from day 1 to 10. The cumulative residual for days 1 to 10 is -2.8% with a test statistic of -3.85. This study finds as PS that there is some anticipation for both upgrades and downgrades. It extends their work by statistically testings the reversals after the announcement date and by testing the announcement day effect. There is significant abnormal return for the downgrades on the announcement day and the upgrades have a significant reversal in their residuals from day 1 to 10. This provides both support and extension of Griffin and Sanvicente's results and suggests that Moody's is offering the market new information.