Social Media TV

Google Tech Talks
December 16, 2008

ABSTRACT

Graph identification refers to methods that transform observational data described as a noisy, input graph into an inferred “clean” output graph. Examples include inferring social networks from communication data, identifying gene regulatory networks from protein-protein interactions, etc. On the flip-side, there is a growing interest in anonymizing social network data, and understanding the different types of privacy threats inherent in relational data. In this talk, I will discuss some of the key processes involved in identification (entity resolution, link prediction, collective classification and group detection) and I will overview results showing that on several well-known social media sites, we can easily and accurately recover information that users may wish to remain private.

Speaker: Lise Getoor
Lise Getoor is an associate professor in the Computer Science Department at the University of Maryland, College Park. She received her PhD from Stanford University in 2001. Her current work includes research on link mining, statistical relational learning and representing uncertainty in structured and semi-structured data. She has published numerous articles in machine learning, data mining, database, and artificial intelligence forums. She was awarded an NSF Career Award, is an action editor for the Machine Learning Journal, a JAIR associate editor, has been a member of AAAI Executive council, and has served on a variety of program committees including AAAI, ICML, IJCAI, KDD, SIGMOD, UAI, VLDB, and WWW. More information can be found at www.cs.umd.edu/~getoor

Duration : 0:56:31

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Google Tech Talks
February, 28 2008

ABSTRACT

NetTrust is a system that embeds social context in browsing by combining individual histories, social networks, and explicit ratings. NetTrust combines an implicit and explicit means of data collection. This trust based system uses shared browsing histories from a user’s self-selected social networks to create both explicit and implicit data collection. NetTrust targets the human element of trust. It projects how a social network can signal meaningful trust information that can make an educative browsing experience. NetTrust allows an individual to select their own trusted sources of information and rate particular sites as trustworthy (or not). NetTrust allows an individual to select their own trusted authoritative sources of information from a market of ratings agencies and combine these ratings with the reputation information from their individual social network. This paper will present the Net Trust system; the dorm-based homophily tests with implications and the undergraduate-focused user testing.

Speaker: Professor L. Jean Camp
Professor L. Jean Camp is the author of Trust and Risk in Internet Commerce (MIT Press), Economics of Identity Theft (Springer) and the editor of Economics of Information Security (Kluwer Academic). She has authored over one hundred works, including seventy peer-reviewed works and eighteen book chapters. In addition to presentations at peer-reviewed venues, she has made scores of invited presentations on four continents. Her service has included the Board of Directors of Computer Professionals for Social Responsibility, the Board of Governors of the IEEE Society on Social Implications of Technology, Senior Member of the IEEE, and longstanding member of the USACM. See http://www.ljean.com/cv.html for more detailed information and full text of various publications.

Duration : 0:57:20

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Google Tech Talks
January 14, 2009

ABSTRACT

Website: http://www.doyoupoken.com

Picture yourself on a university campus, or in a bar. You come across some friends, and meet some new people with whom you would like stay in touch. Instead of jotting down each person’s email address, you simply pull your Poken out of your pocket and touch it against the other person’s Poken. Next time you log in to your favorite social network, your profiles are linked and you can access enhanced functionality and services such as viewing your social interactions in a timeline.

Poken is building a service as yet unseen on the Internet, that fits right in with the move towards more open, easily accessible social networks. Combining a low-cost designer keychain accessory, containing our patented RF communication technology, and an open web-based API, we provide the tools that enable any social network to extend their reach into the real world.

Speaker: Stephane Doutriaux
In 1999 Stephane launched a Montreal-based internet start-up developing algorithms for on-demand delivery of high-fidelity audio over digital cable networks. Following this early career experience he held various positions in the high-tech industry in Canada, France and Spain. He recently completed an MBA at Switzerlands Institute for Management Development (IMD). In 2007, Stephane grew a virtual cosmetics company and sold it to the board of LOreal, as part of the e-Strat International Business Strategy Competition.

Duration : 0:46:27

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