Group items tagged

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.

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

In comparison, Google spent $3.76 million in the last quarter of 2011. The increased outreach to policymakers appears to be an industry trend.

Social networks are flooded with potential customers.

A social business engages the entire company, from CEO to executive assistant. Take advantage of the opportunity to foster your company’s internal community and teach valuable social media skills as the space rapidly grows and evolves.

Abstract Tools for social networking and social awareness are developing rapidly and evolving continuously. They are gaining popularity in a growing number of professional as well as personal activities, including scholarly research. There are social awareness tools for science researchers that facilitate collaboration, help manage references, and offer options for presenting findings in new ways. This paper discusses those tools. Evaluating and understanding their functionalities requires effort, and scientists can be reluctant to invest the necessary time to learn to use and populate them on their own. This suggests that an important role for librarians is to evaluate the many social awareness tools available, to recommend the ones that are best suited to each researcher's needs, and to help researchers use those tools effectively.