959 resultados para user generated services
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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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Relatório de estágio apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel
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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores
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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.
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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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Este proyecto nace de la necesidad de realizar una integración de los sistemas informáticos de una empresa en una multinacional; las empresas disponen de servicios de outsourcing en sistemas de información. Al tratarse de una integración operativa, sólo trataremos de trasladar los servicios de centro de atención al usuario, soporte local y ofimática desde un outsourcing de servicios a otro, añadiendo los cambios de procesos necesarios para disponer de un único entorno de trabajo. El cambio de entorno de trabajo se ha de realizar sin perdida de disponibilidad ni de información.
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Learning is changing. A pivotal force in bringing about this change is the use of information and communications technology (ICT) which provides richer, more immediate, world-relevant educational resources and opportunities. When used well, ICT enriches learning and enhances teaching. It invigorates classroom activities and is a powerful motivational tool that encourages learners to progress in more personalised and self-directed ways. Ireland has achieved rapid change and growth in the past decade, but to sustain this we must prepare the next generation for the knowledge society in which they will live. The challenge we face is to ensure that the emphasis on ICT in schools shifts, in the immediate future, from technology provision to a focus on its deliberate use by the learner. Fostering personal creativity has always been a desirable educational value. The pursuit of creativity and inventiveness are now pivotal skills in a knowledge economy and the embedding of ICT in learning can greatly facilitate their development. Web 2.0 will facilitate greater interactivity and enable greater levels of user-generated content. It is crucial that young people acquire the ICT and related skills to support these new opportunities.
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User generated content shared in online communities is often described using collaborative tagging systems where users assign labels to content resources. As a result, a folksonomy emerges that relates a number of tags with the resources they label and the users that have used them. In this paper we analyze the folksonomy of Freesound, an online audio clip sharing site which contains more than two million users and 150,000 user-contributed sound samplescovering a wide variety of sounds. By following methodologies taken from similar studies, we compute some metrics that characterize the folksonomy both at the globallevel and at the tag level. In this manner, we are able to betterunderstand the behavior of the folksonomy as a whole, and also obtain some indicators that can be used as metadata for describing tags themselves. We expect that such a methodology for characterizing folksonomies can be useful to support processes such as tag recommendation or automatic annotation of online resources.
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El presente proyecto de investigación se presenta como trabajo final del Máster en Estudis Avançats en Comunicació Social y pretende sentar las bases de la futura tesis doctoral. Se plantea una investigación que tiene como objetivo determinar la capacidad que tuvo el uso de las redes digitales de comunicación para modificar la esfera pública durante la primavera árabe en Túnez y el posterior proceso de Transición llevado a cabo. Para ello la investigación se aborda desde tres conceptos clave: el pluralismo mediático, la relevancia mediàtica y los procesos comunicativos. La investigación se abordará triangulando los métodos cuantitativo y cualitativo y se propone como técnica el anàlisis de contenido sobre la nueva legislación tunecina en materia de Políticas de Comunicación, así como del contenido generado por los usuarios en las redes digitales de comunicación y las noticias de medios de referencia online árabes (3) y occidentales (4) en relación con el objeto de estudio.
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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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Tässä työssä selvitetään mitä mobiiliympäristössä käytettävillä kontekstitietoisilla sovelluksilla tarkoitetaan, miksi niitä tarvitaan ja mitä niiden avulla voidaan saavuttaa. Käyttäjäkeskeisen palvelun tavoitteena on mukautua käyttäjän kontekstiin, sekä hänen tarpeisiin ja tavoitteisiin ilman käyttäjältä vaadittavaa jatkuvaa vuorovaikutusta. Kontekstitietoisen sovelluksen suunnittelussa ja toteutuksessa tulee kiinnittää huomiota muun muassa kontekstitiedon keräämiseen, tallentamiseen ja tiedon eheyden säilyttämiseen. Sovelluksen suunnittelun tärkein haaste on toteuttaa hyvä logiikka, joka osaa päätellä kontekstitiedoista mitä toimintoja sen tulisi suorittaa. Mobiilipalveluiden personalisoinnissa on tärkeää ottaa huomioon käyttäjän, laitteen ja palvelun väliset vuorovaikutussuhteet. Nämä vuorovaikutussuhteet määrittelevät miten tiettyä mobiilipalvelua tulisi personalisoida jotta palvelu pystyy täyttämään käyttäjän sille asettamat vaatimukset.
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Työn tavoitteena oli kokonaisnäkemyksen luominen Helsingin seudun liikenteenhallinnan tilasta ja kehitysnäkymistä sekä seuraavien tärkeimpien kehittämispolkujen tunnistaminen ja konkretisointi toimenpiteiksi. Työssä keskityttiin seuraaviin painopistealueisiin 1. Liityntäpysäköinnin informaation ja maksujärjestelmien kehittäminen 2. Liikenteenhallintakeskuksen toiminnan kehittäminen ja laajentaminen 3. Liikennejärjestelmän reaaliaikainen tilannekuva ja lyhyen aikavälin ennusteet 4. Pääkaupunkiseudun pääväylien ruuhkien ja häiriöiden hallinta 5. Joukkoliikenteen ajantasaisen matkustajainformaation kehittäminen. Työssä laadittiin katsaus kullakin painopistealueella jo tapahtuneeseen sekä käynnissä olevaan kehitystyöhön, kuvattiin esiin nousseita ongelmia ja laadittiin esitys vuoteen 2020 ulottuvasta toiminnallisesta tavoitetilasta sekä konkreettisista kehittämistoimista. Työssä järjestettiin myös tulevaisuustyöpaja, johon pyydettiin alustuksia valikoiduilta viranomaistahoilta, tutkijoilta ja palveluntuottajilta. Näiden keskustelujen kautta kirkastettiin seudun toimijoiden näkemystä älyliikenteen toimialan kehitysnäkymistä ja –tarpeista. Työn lopputuloksena syntyneeseen toimenpideohjelmaan kirjattiin yhteensä 30 hanketta. Näistä viisi hanketta valittiin työpajatyöskentelyn kautta varsinaisiksi kärkihankkeiksi, joiden toteutus on kriittistä liikkujien ja viranomaistyön palvelutason kannalta ja joka edellyttää usean toimijan yhteistyötä. Lisäksi tunnistettiin joukko seurattavia hankkeita. Valitut kärkihankkeet, käynnistämisen vastuutaho sekä tavoitteellinen käynnistysvuosi ovat seuraavat: 1. Liityntäpysäköinnin dynaamisen informaatiojärjestelmän pilotointi Hämeenlinnanväylän käytävässä Kehäradan asemilla (HSL 2012) 2. HSL:n alueen joukkoliikenteen häiriönhallinnan uudelleenorganisointi (HSL, Liikennevirasto 2012) 3. Seudullisen liikenteenhallintasuunnitelman laadinta verkollisen operoinnin kehittämiseksi häiriötilanteissa (ELY-keskus, Liikennevirasto 2013) 4. Reaaliaikaisen sujuvuustiedon tuottaminen ruuhkautuvalta pääkatu- ja alempiasteiselta maantieverkolta (Liikennevirasto, kunnat 2012) 5. Liikenteen vaihtuvan ohjauksen ja tiedottamisen hyödyntäminen pääväylien ruuhkautumisen ja häiriöiden hallinnassa. (ELY-keskus 2012) Kärkihankkeisiin ei liity sellaisia riippuvuuksia, että niitä ei voitaisi käynnistää ennen päätöksentekoa jostakin muusta investoinnista. Merkittävimmät riippuvuudet liittyvät LIJ2014-järjestelmän ajoneuvojen paikannuksen ja muiden työkalujen valmistumiseen. Johtoryhmän linjauksen mukaan kärkihankkeissa ja muissakin toimijoiden omissa hankkeissa syntyvien tietojärjestelmien rajapinnat avataan soveltuvasti kaupallisten toimijoiden käyttöön, jolloin syntyvien kaupallisten loppukäyttäjäpalveluiden kautta voidaan parantaa tietopalvelujen tavoittavuutta. Kärkihankkeiden valinta ja sisältö on rakennettu pitkälti sen lähtökohdan varaan, että liikenteen tietopalveluissa julkistoimijoiden roolina on pääasiassa lähtötietojen tuottaminen ja jakaminen varsinaisille palveluntuottajille. Vuoteen 2016 mennessä uusien rajapintojen kautta jaettavien tietojen määrä on nykyiseen verrattuna huomattavasti laajempi, ja odotukset uusien ja innovatiivisten palvelujen syntymiselle ovat korkeat. HLH-johtoryhmä nimeää jokaisen kärkihankkeen läpiviennistä vastaavan työryhmän, joiden työskentelyä ohjataan nykyisen kaltaisessa johtoryhmätyössä. Johtoryhmätyön organisointi on todettu toimivaksi, sillä ryhmä koostuu seudun 14 kunnan alueen keskeisistä julkisista toimijoista ja sen kautta on olemassa vahvat kytkennät sekä seudun liikennejärjestelmätyöhön (HLJ) että valtakunnalliseen älyliikenteen kehitystyöhön.
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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.