4,652 research outputs found

    Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ

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    Scattertext is an open source tool for visualizing linguistic variation between document categories in a language-independent way. The tool presents a scatterplot, where each axis corresponds to the rank-frequency a term occurs in a category of documents. Through a tie-breaking strategy, the tool is able to display thousands of visible term-representing points and find space to legibly label hundreds of them. Scattertext also lends itself to a query-based visualization of how the use of terms with similar embeddings differs between document categories, as well as a visualization for comparing the importance scores of bag-of-words features to univariate metrics.Comment: ACL 2017 Demos. 6 pages, 5 figures. See the Githup repo https://github.com/JasonKessler/scattertext for source code and documentatio

    Topic Similarity Networks: Visual Analytics for Large Document Sets

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    We investigate ways in which to improve the interpretability of LDA topic models by better analyzing and visualizing their outputs. We focus on examining what we refer to as topic similarity networks: graphs in which nodes represent latent topics in text collections and links represent similarity among topics. We describe efficient and effective approaches to both building and labeling such networks. Visualizations of topic models based on these networks are shown to be a powerful means of exploring, characterizing, and summarizing large collections of unstructured text documents. They help to "tease out" non-obvious connections among different sets of documents and provide insights into how topics form larger themes. We demonstrate the efficacy and practicality of these approaches through two case studies: 1) NSF grants for basic research spanning a 14 year period and 2) the entire English portion of Wikipedia.Comment: 9 pages; 2014 IEEE International Conference on Big Data (IEEE BigData 2014

    Analysis and Forecasting of Trending Topics in Online Media Streams

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    Among the vast information available on the web, social media streams capture what people currently pay attention to and how they feel about certain topics. Awareness of such trending topics plays a crucial role in multimedia systems such as trend aware recommendation and automatic vocabulary selection for video concept detection systems. Correctly utilizing trending topics requires a better understanding of their various characteristics in different social media streams. To this end, we present the first comprehensive study across three major online and social media streams, Twitter, Google, and Wikipedia, covering thousands of trending topics during an observation period of an entire year. Our results indicate that depending on one's requirements one does not necessarily have to turn to Twitter for information about current events and that some media streams strongly emphasize content of specific categories. As our second key contribution, we further present a novel approach for the challenging task of forecasting the life cycle of trending topics in the very moment they emerge. Our fully automated approach is based on a nearest neighbor forecasting technique exploiting our assumption that semantically similar topics exhibit similar behavior. We demonstrate on a large-scale dataset of Wikipedia page view statistics that forecasts by the proposed approach are about 9-48k views closer to the actual viewing statistics compared to baseline methods and achieve a mean average percentage error of 45-19% for time periods of up to 14 days.Comment: ACM Multimedia 201

    Application of serious games to sport, health and exercise

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    Use of interactive entertainment has been exponentially expanded since the last decade. Throughout this 10+ year evolution there has been a concern about turning entertainment properties into serious applications, a.k.a "Serious Games". In this article we present two set of Serious Game applications, an Environment Visualising game which focuses solely on applying serious games to elite Olympic sport and another set of serious games that incorporate an in house developed proprietary input system that can detect most of the human movements which focuses on applying serious games to health and exercise

    Olympic Landscapes: A Global Event on a Local Landscape

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    Recently, cities around the globe have become involved in a competition for obtaining the title of the most “powerful” city in the world. Hosting mega-events, like the Olympics allow for these cities to restructure the entire floor plan of their metropolis. The Olympic games are well-known global events that occur within a smaller scale local landscape; therefore, the landscape undergoes many changes due to the drastic measures the games entail, as well as the goals for the landscape, economy, and residents post-Olympics. While looking at these landscapes, it is important to remember that the individual shapes the landscape, while the landscape itself influences and shapes the individuals who reside there (Tilley 1996:162). The landscape of the Olympics is structured around human desires and political interests, while in turn, the reconstructed landscape, reshapes the memories, meanings, and conceptions the residents associate with the area itself. The built landscape of the Olympic can be understood as a conceptual, ideational, and a constructed landscape through the instilled memories, political associations, aesthetic appeal, and the outcomes of the newly shaped area. In this paper I analyze the Olympics in terms of its effects on a city by using analytical categories of conceptual, ideational, and a constructed landscape. I consider the desirability of becoming host city, the transformation of the land not only to support the event itself, but also in relation to the functioning use of the land post-Olympic, as well as how monuments, places, and cohesive events instill a stronger sense of social solidarity and unity through emotional connections

    Evaluating Cartogram Effectiveness

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    Cartograms are maps in which areas of geographic regions (countries, states) appear in proportion to some variable of interest (population, income). Cartograms are popular visualizations for geo-referenced data that have been used for over a century and that make it possible to gain insight into patterns and trends in the world around us. Despite the popularity of cartograms and the large number of cartogram types, there are few studies evaluating the effectiveness of cartograms in conveying information. Based on a recent task taxonomy for cartograms, we evaluate four major different types of cartograms: contiguous, non-contiguous, rectangular, and Dorling cartograms. Specifically, we evaluate the effectiveness of these cartograms by quantitative performance analysis, as well as by subjective preferences. We analyze the results of our study in the context of some prevailing assumptions in the literature of cartography and cognitive science. Finally, we make recommendations for the use of different types of cartograms for different tasks and settings
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