The Web Scene » Social

New Social Networking Tool to Improve Well-Being Awareness

sparky3887 — Thu, 19 Nov 2009 01:12:00 +0000

A social networking tool called Healthii has improved personal and group well-being and interactions, according to researchers at the University of Southampton’s School of Electronics and Computer Science. A study of 10 Healthii users over five weeks reveals that half felt they were more reflective, eight said they were more aware of other group members, and half said they would really miss this level of communication when the trial ended. Healthii was designed to help users of social networking sites and microblogs understand how they and their peers are doing, and to help them enhance their quality of life at work. The application uses graphical avatars to show the level of busy-ness, enjoyment, stress, and health of users, and adding a numeric code would allow a person to quickly communicate that he or she is feeling very busy, enjoying the task, averagely stressed, but feeling a bit under the weather, for example. The field of Human-Computer Interaction tends to focus on designing to support efficiency or productivity in tasks, says dr schraefel. “That’s important, but we’re now beginning to consider how to design systems to support well-being while engaged in everyday tasks to enhance quality of life,” says schraefel. “Eventually, we hope to inspire designers and researchers not only to explore these attributes in social networking applications, but also to consider the potential for well-being measures across Human-Computer Interaction the same way we consider efficiency today,” says Ph.D. student Paul Andre.

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Social Networking Meets Ambient Intelligence

sparky3887 — Thu, 05 Nov 2009 01:07:26 +0000

European researchers working on the ASTRA project are combining the instant sharing capabilities of social networking with emerging ambient intelligence systems that use sensors and smart objects to create an awareness of a user’s activities. The researchers say that combining the two technologies could create a new way to stay in touch with friends and relatives. The ASTRA system would use smart objects and sensors distributed throughout a person’s office or home to continually update their status information, automatically informing friends and families if a user is busy in a meeting or doing a chore and unable to answer the phone, for example. “Not only is this information generated automatically, depending on the criteria set by each user, but it does not have to be displayed on a computer screen or in any other distracting way,” says the Research Academic Computer Technology Institute’s Achilles Kameas. “In a smart home or office environment, the system could let users know if someone is available for a phone call or not simply by changing the color of the frame of a photo of them.” Phillips Electronics and mobile operator Telenor are conducting trials of the ASTRA technology, and Kameas says the response from test users has been positive, though some have raised concerns about privacy and security issues. He says the ASTRA system is similar to Facebook in that users can determine how much information is shared and who has access to that information. The researchers plan to launch a follow-up initiative for adaptive pervasive awareness systems based on the concept of a trustworthy personal “bubble” to ensure privacy.

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Weakness in Social Security Numbers Is Found

sparky3887 — Thu, 09 Jul 2009 16:02:14 +0000

Carnegie Mellon University researchers have demonstrated that Social Security numbers (SSNs) can be predicted based solely on an individual’s date and location of birth using statistical techniques. They describe their research in the Proceedings of the National Academy of Sciences as “an unexpected consequence of the interaction between multiple data sources, trends in information exposure, and antifraud policy initiatives with unintended effects.” The discovery makes the U.S. Social Security numbering system vulnerable to fraud, with the researchers noting that it is now possible to regularly reconstruct sensitive personal information from the kind of online postings often found on social networking sites and other online sources. The researchers used an algorithm on 500,000 publicly available records in the Social Security Administration’s Death Master File to successfully identify statistical patterns that then allowed extrapolation to the living U.S. population, making it possible to identify millions of SSNs for individuals whose birth date and location were a matter of public record. The researchers’ sample showed that it was possible to identify in a single attempt the first five digits for 44 percent of deceased individuals who were born after 1988 and for 7 percent of those born from 1973 to 1988, while the identification of all nine digits for 8.5 percent of those born after 1988 was possible in less than 1,000 tries. The prediction system’s accuracy rose for smaller states and for individuals born after 1988 on account of rules that led increasingly to the designation of Social Security numbers at birth. Mark Lassiter with the Social Security Administration has downplayed the significance of the researchers’ conclusions, calling their findings “an exaggeration.”

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