949 resultados para user generated content


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This dissertation research points out major challenging problems with current Knowledge Organization (KO) systems, such as subject gateways or web directories: (1) the current systems use traditional knowledge organization systems based on controlled vocabulary which is not very well suited to web resources, and (2) information is organized by professionals not by users, which means it does not reflect intuitively and instantaneously expressed users’ current needs. In order to explore users’ needs, I examined social tags which are user-generated uncontrolled vocabulary. As investment in professionally-developed subject gateways and web directories diminishes (support for both BUBL and Intute, examined in this study, is being discontinued), understanding characteristics of social tagging becomes even more critical. Several researchers have discussed social tagging behavior and its usefulness for classification or retrieval; however, further research is needed to qualitatively and quantitatively investigate social tagging in order to verify its quality and benefit. This research particularly examined the indexing consistency of social tagging in comparison to professional indexing to examine the quality and efficacy of tagging. The data analysis was divided into three phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of tag attributes. Most indexing consistency studies have been conducted with a small number of professional indexers, and they tended to exclude users. Furthermore, the studies mainly have focused on physical library collections. This dissertation research bridged these gaps by (1) extending the scope of resources to various web documents indexed by users and (2) employing the Information Retrieval (IR) Vector Space Model (VSM) - based indexing consistency method since it is suitable for dealing with a large number of indexers. As a second phase, an analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. Finally, to investigate tagging pattern and behaviors, a content analysis on tag attributes was conducted based on the FRBR model. The findings revealed that there was greater consistency over all subjects among taggers compared to that for two groups of professionals. The analysis of tagging exhaustivity and tag specificity in relation to tagging effectiveness was conducted to ameliorate difficulties associated with limitations in the analysis of indexing consistency based on only the quantitative measures of vocabulary matching. Examination of exhaustivity and specificity of social tags provided insights into particular characteristics of tagging behavior and its variation across subjects. To further investigate the quality of tags, a Latent Semantic Analysis (LSA) was conducted to determine to what extent tags are conceptually related to professionals’ keywords and it was found that tags of higher specificity tended to have a higher semantic relatedness to professionals’ keywords. This leads to the conclusion that the term’s power as a differentiator is related to its semantic relatedness to documents. The findings on tag attributes identified the important bibliographic attributes of tags beyond describing subjects or topics of a document. The findings also showed that tags have essential attributes matching those defined in FRBR. Furthermore, in terms of specific subject areas, the findings originally identified that taggers exhibited different tagging behaviors representing distinctive features and tendencies on web documents characterizing digital heterogeneous media resources. These results have led to the conclusion that there should be an increased awareness of diverse user needs by subject in order to improve metadata in practical applications. This dissertation research is the first necessary step to utilize social tagging in digital information organization by verifying the quality and efficacy of social tagging. This dissertation research combined both quantitative (statistics) and qualitative (content analysis using FRBR) approaches to vocabulary analysis of tags which provided a more complete examination of the quality of tags. Through the detailed analysis of tag properties undertaken in this dissertation, we have a clearer understanding of the extent to which social tagging can be used to replace (and in some cases to improve upon) professional indexing.

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Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

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This article aims to discuss the role humour plays in politics, particularly in a media environment overflowing with user-generated video. We start with a genealogy of political satire, from classical to Internet times, followed by a general description of “the Downfall meme,” a series of videos on YouTube featuring footage from the film Der Untergang and nonsensical subtitles. Amid video-games, celebrities, and the Internet itself, politicians and politics are the target of such twenty-first century caricatures. By analysing these videos we hope to elucidate how the manipulation of images is embedded in everyday practices and may be of political consequence, namely by deflating politicians' constructed media image. The realm of image, at the centre of the Internet's technological culture, is connected with decisive aspects of today's social structure of knowledge and play. It is timely to understand which part of “playing” is in fact an expressive practice with political significance.

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A quantidade e variedade de conteúdos multimédia actualmente disponíveis cons- tituem um desafio para os utilizadores dado que o espaço de procura e escolha de fontes e conteúdos excede o tempo e a capacidade de processamento dos utilizado- res. Este problema da selecção, em função do perfil do utilizador, de informação em grandes conjuntos heterogéneos de dados é complexo e requer ferramentas específicas. Os Sistemas de Recomendação surgem neste contexto e são capazes de sugerir ao utilizador itens que se coadunam com os seus gostos, interesses ou necessidades, i.e., o seu perfil, recorrendo a metodologias de inteligência artificial. O principal objectivo desta tese é demonstrar que é possível recomendar em tempo útil conteúdos multimédia a partir do perfil pessoal e social do utilizador, recorrendo exclusivamente a fontes públicas e heterogéneas de dados. Neste sen- tido, concebeu-se e desenvolveu-se um Sistema de Recomendação de conteúdos multimédia baseado no conteúdo, i.e., nas características dos itens, no historial e preferências pessoais e nas interacções sociais do utilizador. Os conteúdos mul- timédia recomendados, i.e., os itens sugeridos ao utilizador, são provenientes da estação televisiva britânica, British Broadcasting Corporation (BBC), e estão classificados de acordo com as categorias dos programas da BBC. O perfil do utilizador é construído levando em conta o historial, o contexto, as preferências pessoais e as actividades sociais. O YouTube é a fonte do histo- rial pessoal utilizada, permitindo simular a principal fonte deste tipo de dados - a Set-Top Box (STB). O historial do utilizador é constituído pelo conjunto de vídeos YouTube e programas da BBC vistos pelo utilizador. O conteúdo dos vídeos do YouTube está classificado segundo as categorias de vídeo do próprio YouTube, sendo efectuado o mapeamento para as categorias dos programas da BBC. A informação social, que é proveniente das redes sociais Facebook e Twit- ter, é recolhida através da plataforma Beancounter. As actividades sociais do utilizador obtidas são filtradas para extrair os filmes e séries que são, por sua vez, enriquecidos semanticamente através do recurso a repositórios abertos de dados interligados. Neste caso, os filmes e séries são classificados através dos géneros da IMDb e, posteriormente, mapeados para as categorias de programas da BBC. Por último, a informação do contexto e das preferências explícitas, através da classificação dos itens recomendados, do utilizador são também contempladas. O sistema desenvolvido efectua recomendações em tempo real baseado nas actividades das redes sociais Facebook e Twitter, no historial de vídeos Youtube e de programas da BBC vistos e preferências explícitas. Foram realizados testes com cinco utilizadores e o tempo médio de resposta do sistema para criar o conjunto inicial de recomendações foi 30 s. As recomendações personalizadas são geradas e actualizadas mediante pedido expresso do utilizador.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores

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This study examined user-generated (UG) advertising in the context of social media networks. The focus was on how people, whether an expert in the area, a non-expert or a friend, influence the reader of the advertisement. Furthermore, the study analyzed how the certainty level of the UG advertisement influences the person viewing the ad. The study showed that for the friend source a high certainty message was more persuasive. However, regarding the certainty no significant results were found for the expert and non-expert. Further, the type of the source had a considerable impact on persuasion. Someone that we personally know (e.g., a friend) was rated most positive for all analyzes variables. This shows that with the rising usage of social media there are great opportunities for new effective advertising strategies that could include a new type of an endorser – friends.

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A nutrição e a alimentação. Dois conceitos tão pessoais quanto públicos, que geram discussão e abrem espaço a mitos e crenças. O interesse coletivo nestes assuntos é causa e consequência da grande quantidade de informação, por vezes pouco rigorosa, outras contraditória, disponível online. Impõe-se portanto não só a transmissão de informação fidedigna, que reflita o estado atual da ciência, mas também a criação de espaços de diálogo, capazes de suscitar sentido crítico, num contexto de interação e comunicação online. Contextualiza-se assim a relevância do projeto QEAT, uma plataforma de comunicação de ciência, assente numa matriz de Envolvimento Público da Ciência ou Public Engagement with Science (PES), na sua expressão em inglês. O QEAT pretende ser um espaço de referência online, que promove o diálogo ao serviço da informação sobre alimentação e nutrição. Uma plataforma onde há espaço para o esclarecimento, a discussão e a participação, reunindo especialistas e não especialistas na mesma missão de comunicar nutrição. O modelo eleito seguirá um formato de rede social de pergunta e resposta (SQ&A), aproveitando a interatividade e a transversalidade destes canais de comunicação, abrindo aos diferentes públicos a possibilidade de participar na plataforma com perguntas, ideias, conteúdos. Desta forma, as ciências da nutrição e alimentação serão o tópico dominante das conversas, abertas a todos os interessados, instigadas e moderadas pelos gestores da plataforma. O canal QEAT será alimentado por conteúdos coproduzidos por nutricionistas, cientistas e diferentes profissionais da comunicação, no âmbito do projeto, a par de conteúdos produzidos pelos utilizadores (user generated contents), sujeitos a uma votação, ou seja, um controlo de qualidade. Todos os contribuidores vão construindo a sua reputação de acordo com a validade dos conteúdos que produzem. Uma gestão de conteúdos que permite por um lado monitorizar a qualidade e o rigor da informação, mas também perceber os tópicos que interessam aos utilizadores, bem como as suas dúvidas. A implementação deste projeto procura criar um espaço de referência online capaz de funcionar como um repositório dinâmico de informação sobre nutrição; e fomentar uma relação bidirecional entre os diferentes públicos do projeto. Da persecução destes objetivos, espera-se que resultem novas ideias, conhecimentos e direções dos caminhos a tomar no sentido de uma comunicação responsável na área da nutrição.

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No quadro da investigação científica sobre rádio, os últimos anos têm dado a conhecer inúmeras abordagens sobre o significado de uma post-radio (Oliveira & Portela, 2011), isto é, a definição de um conjunto de questões que se colocam à inclusão da rádio contemporânea em ambientes digitais e online. Esta migração digital tem vindo a proporcionar o desenvolvimento das aplicações móveis das rádios, como o alargamento das potencialidades comunicativas (Aguado, Feijoo & Martínez, 2013), de audiências, de convergência de conteúdos interativos entre ouvintes-utilizadores. Conscientes desta oportunidade, as principais emissoras da Espanha e Portugal alargaram o universo da radiofonia à plataforma móvel, com especial atenção aos telefones inteligentes, através do desenvolvimento de aplicações móveis (apps) (Cerezo, 2010). Os smartphones, como símbolo de uma cultura em permanente mutação, sugerem não apenas uma maior facilidade no acesso e interação, mas acrescentam grandes possibilidades para a difusão de conteúdos entre audiências, o que estudos têm designado por user distributed content (Villi, 2012). O presente artigo apresenta uma análise exploratória sobre as políticas atuais das principais rádios espanholas e portuguesas nas aplicações móveis, avaliando o grau de interação e participação mobilizado nessas plataformas. Durante a observação, conclui-se, entre outros dados, que a plataforma móvel representa um canal suplementar para a rádio tradicional FM, mais que um novo meio com linguagem e expressividade próprios.

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Internet-verkon sisältöpalvelut ovat viime vuosina kehittyneet siten, että yhä suurempi osa sisällöstä on käyttäjäyhteisön itse tuottamaa. Esimerkkejä tällaisista uusista palveluista ovat verkkopäiväkirjat eli blogit, valokuva- ja videotietokannat Flickr ja YouTube sekä nk. wiki- sivustot. kuten Wikipedia-tietosanakirja. Tässä työssä tutkittiin, onko vastaavaa sisällöntuotannon muutosta tapahtunut avoimissa alueverkoissa. Työssä myös esitetään eräät määritelmät avoimille ja operaattorineutraaleille verkoille. Toisena tavoitteena oli tutkia, hyödynnetäänkö avoimien alueverkkojen palveluissa verkon alueellisuutta. Työ toteutettiin kyselytutkimuksina alueverkkojen ylläpitäjille sekä käyttäjille. Kyselystä saatujen tulosten mukaan avoimissa alueverkoissa ei ole laajalti tarjolla käyttäjälähtöisiä sisältöpalveluja, mutta paikallisuutta hyödyntäviä palveluja on tarjolla. Toisaalta kyselytulosten mukaan käyttäjät toivovatkin alueverkoilta nimenomaan paikallisuutta hyödyntäviä palveluja. Käyttäjälähtöisiä sisältöpalveluja käytetään runsaasti, mutta ilmeisesti laajemman Internet-verkon tasolla.

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Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

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Increasing usage of Web Services has been result of efforts to automate Web Services discovery and interoperability. The Semantic Web Service descriptions create basis for automatic Web Service information management tasks such as discovery and interoperability. The discussion of opportunities enabled by service descriptions have arisen in recent years. The end user has been considered only as a consumer of services and information sharing occurred from one service provider to public in service distribution. The social networking has changed the nature of services. The end user cannot be seen anymore only as service consumer, because by enabling semantically rich environment and right tools, the end user will be in the future the producer of services. This study investigates the ways to provide for end users the empowerment to create service descriptions on mobile device. Special focus is given to the changed role of the end user in service creation. In addition, the Web Services technologies are presented as well as different Semantic Web Service description approaches are compared. The main focus in the study is to investigate tools and techniques to enable service description creation and semantic information management on mobile device.

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The objective of this Bachelor's Thesis is to find out the role of social media in the B-to-B marketing environment of the information technology industry and to discover how IT-firms utilize social media as a part of their customer reference marketing. To reach the objectives the concepts of customer reference marketing and social media are determined. Customer reference marketing can be characterized as one of the most practically relevant but academically relatively overlooked ways in which a company can leverage its customers and delivered solutions and use them as references in its marketing activities. We will cover which external and internal functions customer references have, that contribute to the growth and performance of B-to-B firms. We also address the three mechanisms of customer reference marketing which are 'status transfer', 'validation through testimonials' and 'demonstration of experience and prior performance'. The concept of social media stands for social interaction and creation of user-based content which exclusively occurs through Internet. The social media are excellent tools for networking because of the fast and easy access, easy interaction and vast amount of multimedia attributes. The allocation of social media is determined. The case company helps clarify the specific characteristics of social media usage as part of customer-reference-marketing activities. For IT-firms the best channels to utilize social media in their customer reference marketing activities are publishing and distribution services of content and networking services.

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This study discusses the procedures of value co-creation that persist in gaming industry. The purpose of this study was to identify the procedures that persist in current video gaming industry which answers the main research problem how value is co-created in video gaming industry followed by three sub questions: (i) What is value co-creation in gaming industry? (ii) Who participates in value co-creation in gaming industry? (iii) What are the procedures that are involved in value co-creation in gaming industry? The theoretical background of the study consists of literature relating to the theory of marketing i.e., notion of value, conventional understanding of value creation, value chain, co-creation approach, co-production approach. The research adopted qualitative research approach. As a platform of relationship researcher used web 2.0 tool interface. Data were collected from the social networks and netnography method was applied for analyzing them. Findings show that customer and company both co-create optimum level of value while they interact with each other and within the customers as well. However mostly the C2C interaction, discussions and dialogues threads that emerged around the main discussion facilitated to co-create value. In this manner, companies require exploiting and further motivating, developing and supporting the interactions between customers participating in value creation. Hierarchy of value co-creation processes is the result derived from the identified challenges of value co-creation approach and discussion forums data analysis. Overall three general sets and seven topics were found that explored the phenomenon of customer to customer (C2C) and business to customer (B2C) interaction/debating for value co-creation through user generated contents. These topics describe how gamer contributes and interacts in co-creating value along with companies. A methodical quest in current research literature acknowledged numerous evolving flows of value in this study. These are general management perspective, new product development and innovation, virtual customer environment, service science and service dominant logic. Overall the topics deliver various realistic and conceptual implications for using and handling gamers in social networks for augmenting customers’ value co-creation process.

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The thesis analyzes liability of Internet news portals for third-party defamatory comments. After the case of Delfi AS v. Estonia, decided by the Grand Chamber of the European Court of Human Rights on 16 June 2015, a portal can be held liable for user-generated unlawful comments. The thesis aims at exploring consequences of the case of Delfi for Internet news portals’ business model. The model is described as a mixture of two modes of information production: traditional industrial information economy and new networked information economy. Additionally, the model has a generative comment environment. I name this model “the Delfian model”. The thesis analyzes three possible strategies which portals will likely apply in the nearest future. I will discuss these strategies from two perspectives: first, how each strategy can affect the Delfian model and, second, how changes in the model can, in their turn, affect freedom of expression. The thesis is based on the analysis of case law, legal, and law and economics literature. I follow the law and technology approach in the vein of ideas developed by Lawrence Lessig, Yochai Benkler and Jonathan Zittrain. The Delfian model is researched as an example of a local battle between industrial and networked information economy modes. The thesis concludes that this local battle is lost because the Delfian model has to be replaced with a new walled-garden model. Such a change can seriously endanger freedom of expression.