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Resources of Collection 'DA'
You are allowed to see 17 resources in collection DA of user Maschino
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The Structure of Collaborative Tagging Systems
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The Structure of Collaborative Tagging Systems Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge. Scott A. Golder and Bernardo A. Huberman -
Improving Tag-Clouds as Visual Information Retrieval Interfaces
Views: 810 Average Rating:
Improving Tag-Clouds as Visual Information Retrieval Interfaces Tagging-based systems enable users to categorize web resources by means of tags (freely chosen keywords), in order to re-finding these resources later. Tagging is implicitly also a social indexing process, since users share their tags and resources, constructing a social tag index, so-called folksonomy. At the same time of tagging-based system, has been popularised an interface model for visual information retrieval known as Tag-Cloud. In this model, the most frequently used tags are displayed in alphabetical order. This paper presents a novel approach to Tag-Cloud’s tags selection, and proposes the use of clustering algorithms for visual layout, with the aim of improve browsing experience. The results suggest that presented approach reduces the semantic density of tag set, and improves the visual consistency of Tag-Cloud layout. -
Automated Tag Clustering: Improving search and exploration in the tag space
Views: 715 Average Rating:
Automated Tag Clustering: Improving search and exploration in the tag space Grigor Begelman, Philipp Keller, Frank Smadja -
Social Bookmarking Tools (I) A General Review
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Social Bookmarking Tools (I) A General Review Tony Hammond, Timo Hannay, Ben Lund, and Joanna Scott -
Second Generation Tag Clouds joe [at] joelamantia.com -
Tag Clouds Evolve: Understanding Tag Clouds
Views: 438 Average Rating:
Tag Clouds Evolve: Understanding Tag Clouds joe [at] joelamantia.com -
The ESP Game The ESP Game is a two-player game. Each time you play you are randomly paired with another player whose identity you don't know. You can't communicate with your partner, and the only thing you have in common with them is that you can both see the same image. The goal is to guess what your partner is typing on each image. Once you both type the same word(s), you get a new image. Each time you type a word or phrase, you must press enter on your keyboard to submit it to the game. You can type as many guesses as you want, and as soon as a single guess of yours is equal to a guess that your partner has made, you get a new image. You have two and a half minutes to agree on 15 images. Some images have taboo words, which you can't use; nor can you use any plural, singular, or word related to a taboo word. If one of the taboos for an image is the name of a color, you cannot use any other color as a guess. If you feel that an image is too hard, you can ask to pass by clicking the yellow pass button on the lower right corner. Clicking the button will generate a message on your partner's screen, letting them know that you want to pass. You cannot pass on an image until both you and your partner have hit the pass button. -
Audioscrobbler Browser A visualisation tool for finding new music by exploring users' playlists. Audioscrobbler tells you "people who listened to this artist also listened to...". -
liveplasma -
Visualizing Tags over Time Micah Dubinko, Jasmine Novak, Ravi Kumar, Prabhakar Raghavan, Joseph Magnani, Andrew Tomkins -
HT06, Tagging Paper, Taxonomy, Flickr, Academic Article
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HT06, Tagging Paper, Taxonomy, Flickr, Academic Article Cameron Marlow, Mor Naaman, danah boyd, Marc Davis -
Visualizing Social Bookmarks Joris Klerkx, Erik Duval -
Visualizing Social Bookmarks Social bookmarking tools are very popular nowadays. In most tools, users tag the bookmarks to describe them. Therefore, it is often hard for users to discover implicit structures between tags, users and bookmarks. We think that this is essential for both end users to discover new bookmarks that could be of interest to them, and for researchers who want to study how people use social information retrieval tools. In this work, a cluster map visualization application is customized to enable users to explore social bookmarks in the del.icio.us system. The design of the application aims to automatically identify tag and community structures, and visualizes these structures in order to increase the users' awareness of them. Joris Klerkx & Erik Duval -
FOLKSONOMIES AND TAGGING: New developments in social bookmarking
Views: 474 Average Rating:
FOLKSONOMIES AND TAGGING: New developments in social bookmarking Sarah Hayman -
tagging, communities, vocabulary, evolution
Views: 624 Average Rating:
tagging, communities, vocabulary, evolution Sen et al. -
Flickr: Photos tagged with jaguar Flickr has Flickr clusters, which, provided a popular tag, give related tags grouped into clusters. For example, looking at the clusters for the word Jaguar, we see that the clusters neatly fall into several semantic categories of Jaguars: animal, car and plane. The hereby presented guidepost is what makes the difference. Clustering makes it possible to present a guidepost, to provide the means that allow the user to explore the information space. In addition, Flickr also has an interestingness exploration technique which they define as a factor of several parameters including the pageviews, the comments left by users, the specific users, etc. -
Automated Tag Clustering Automated Tag Clustering: Improving search and exploration in the tag space. Grigory Begelman, Philipp Keller, Frank Smadja