Group items tagged

(version PDF en anglais)

La diminution de la circulation de la presse écrite, commencée avec la montée de la télévision, s’accélère avec l’arrivée d’Internet.

C’est dire que l’acte de la transmission doit donc lui-même passer inaperçu, afin de préserver le sentiment qu’un évènement et une information sont une et même chose.

Analytics & Predictive Models for Social Media

Part 1: Information flow in social media (slides) Collecting social media data Extracting and tracking the flow of relevant information Correcting for the effects of missing and incomplete data Predicting and modeling the flow of information Identifying networks of information flow Part 2: Rich user interactions (slides) Predicting and recommending links in network Modeling tie strenght Modeling trust and distrust, frieds and foes How users evaluate one another and the social media content

Despite these individual contributions (which we will revisit in more detail in Section 2), to fully understand tagging systems we believe a holistic approach is necessary. Walker [24] describes tagging as “feral hypertext”, a structure out of control, where the same tag is assigned to different resources with different semantic senses, and thus associates otherwise unrelated resources. However, by considering the entire model, computer systems could make inferences that “domesticate” (to use Walker’s terms) these “feral” tags. For example, tag semantics and synonyms could potentially be inferred by analyzing the structure of the social network, and identifying certain portions of the network that use certain tags for the same resource, or related resources, interchangeably. These tags may be synonymous

Different designs and user incentives can have a major influence on the usefulness of information for various purposes and applications, and in a reciprocal fashion, on how users appropriate and utilize these systems. The design of the system may solicit tagging useful for discovery, retrieval, remembrance, social interaction, or possibly, all of the above

Other likely explanations for the observed correlation between social connection and common tag usage may be found in the descriptive categories of sociolinguistics which studies how different geographic and social formations structure the coherence and diffusion of semantic and syntactic structures in various ”lects” within a larger sociolinguistic system. Some of these example lects include: dialect (a lect used by a geographicallydefined community); sociolect (a lect used by a socially defined community); ethnolect (a lect spoken by a particular ethnic group); ecolect (a lect spoken within a household or family); and idiolect (a lect particular to a certain person). If we conceptualize social tagging systems within the theoretical frame of sociolinguistics, these and other “lects” seem especially applicable to understanding and classifying the apparent isomorphism between social and linguistic structures we observed in Flickr. The structures, changes, and diffusion within and amongst various “lects” in social tagging systems will likely have similar patterns to those found in social network analyses and in sociolinguistic language maps.

Here, we identify several functions tags perform for bookmarks.

The Brave New World of Social Bookmarking : Everything You Always Wanted to Know but Were Too Afraid to Ask

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