6 resultados para Tweet contextualization

em CentAUR: Central Archive University of Reading - UK


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The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

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The work of nouvelliste Annie Saumont constantly explores the phenomenon of memory, and of memories. This article identifies and nuances the various forms that this exploration takes. An introductory contextualization of author and theme is followed by the presentation of a short story, ‘Méandres’, which embodies the first quality of memory to be examined: its capacity not only to recall but also to re-evaluate a past which is thus shown to be as hypothetical as the future. Memory as guilt that moulds or puts its indelible stamp on lives is then evoked by means of examples from other stories, illustrating the gradations Saumont achieves in her investigation of the power of this complex faculty. The next section turns to her portrayal of involuntary memory. Unlike for Proust, the instances of spontaneous remembering that are experienced by her characters lunge at them down the years almost exclusively to wound or disorientate. Depictions of the memory which conserves, and is thus burdened by, secrets are then considered, and finally Saumont's evocation of characters who have different reasons to analyse the way their own and other people's memories work. The conclusion to be drawn is that for Saumont, we are our memories; the ability to master a ‘judicious interpretation’ of memory – or indeed, to forget – is, in her stories, overwhelmingly a quality to be envied.

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This article provides a historical and theoretical contextualization of Amelia Rosselli's practice of translation. Some hitherto neglected Rosselli translations from John Berryman will be examined to ascertain the role played by translation in her multilingual oeuvre. My analysis builds upon recent explorations of translingual authors' translating practice informed by Deleuze and Guattari's seminal Kafka: pour une littérature mineure. It aims to achieve an understanding of the aesthetic of Rosselli's trilingualism and the function of translation within the author's minorizing project.

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The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper.

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Twitter is both a micro-blogging service and a platform for public conversation. Direct conversation is facilitated in Twitter through the use of @’s (mentions) and replies. While the conversational element of Twitter is of particular interest to the marketing sector, relatively few data-mining studies have focused on this area. We analyse conversations associated with reciprocated mentions that take place in a data-set consisting of approximately 4 million tweets collected over a period of 28 days that contain at least one mention. We ignore tweet content and instead use the mention network structure and its dynamical properties to identify and characterise Twitter conversations between pairs of users and within larger groups. We consider conversational balance, meaning the fraction of content contributed by each party. The goal of this work is to draw out some of the mechanisms driving conversation in Twitter, with the potential aim of developing conversational models.

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This editorial introduces a special issue of Food, Culture & Society and works to add a parallel, substantive take on the phenomenon of the food celebrity and the mediated, everyday cultural politics they create. We start by exploring the concept of the foodscape. Specifically, we argue that food celebrities represent a fundamental component of contemporary foodscapes, how they “perform” and function, and the socio-material means by which they are produced. We then explore the key roles and privileges of food celebrity, arguing that the celebrity chef is not the only high-profile, mediating figure at work on the foodscape. Key food celebrity paradoxes are identified and discussed: food celebrities must work to be authentic and aspirational, accessible yet exclusive, responsibilizing but also empowering. We conclude with a short contextualization of the papers in this special issue, and argue for the rich potential of food celebrity scholarship as a way to better understand food inequalities