Messenger taps social nets 
         
        
      By 
      Kimberly Patch, 
      Technology Research News 
       
      If your friends and colleagues don't know 
        the answer to a given question, they often know of a better person to 
        ask. Several teams of researchers are looking to the fast, easy communication 
        of the Internet in order to leverage these social networks.  
         
         Researchers from the University of Michigan have brought the possibilities 
        a step forward with their Small-World Instant Messaging System (SWIM), 
        which extends instant messaging systems by identifying expertise and routing 
        queries accordingly.  
         
         The Small-World Instant Messaging System aims to efficiently tap 
        this expanded network of friends-of-friends, said Jun Zhang, a researcher 
        at the University of Michigan. In trying to use instant messaging and 
        email to get answers from friends and colleagues, Zhang noticed that many 
        times a friend or colleague would defer to one of their friends or colleagues 
        to answer the question. "So I thought why not build a new system to automate 
        this process," he said.  
         
         The system is designed to make it easier to get information that 
        is complicated, too new to be part of an organizational knowledge base, 
        or too valuable for its owners to make it public, said Zhang. The system 
        consists of instant messaging software and a pair of advanced functions 
        that support the social network-based search process, said Zhang.  
         
         First, the program maintains a much more complicated user profile 
        than most instant messengers, said Zhang. "Besides letting a user input 
        his expertise and interests manually, SWIM can automatically mine a user's 
        homepage and browser bookmarks to construct a keyword vector to represent 
        the user's information identity."  
         
         Second, the program contains a referral agent that automatically 
        handles the information-querying process, said Zhang.  
         
         To search for information, a user sends a question to his own 
        referral agent, which broadcasts the query to all of the user's buddies' 
        agents, said Zhang. A referral agent in the buddy's messenger searches 
        its information identity profile to see if that person is likely to be 
        able to answer the question. If not, the agent either returns empty results 
        or forwards the query to its buddies, depending on how the user has set 
        the software.  
         
         When a likely match is found, that person sees the question and 
        the path the query traveled, said Zhang. This friend-of-a-friend or friend-of-a-friend-of-a-friend 
        of the questioner "can either start chatting immediately, or discuss the 
        questions... later if the answering person prefers not to be disturbed 
        at that time," he said.  
         
         There are four challenges to be met in developing this type of 
        software, said Zhang: identifying people's expertise or knowledge from 
        their electronic presence, matching questions to the right people, motivating 
        people to help others, and protecting privacy and avoiding problems with 
        spam.  
         
         The system addresses a very timely issue: quantifying the value 
        of informal social knowledge, said Jon Kleinberg, an associate professor 
        of computer science at Cornell University.  
         
         There are two sides to this, said Kleinberg. "One is the issue 
        of how to find people who have the relevant information." The researchers 
        address this by building navigational techniques into their system, he 
        said. Combining searching with social networks is an interesting idea, 
        he added.  
         
         The more difficult issue is how to get people to participate, 
        Kleinberg said. Friends help friends because they have a relationship, 
        but once the network gets three layers out -- friends of friends of friends 
        -- the person asking for help is a complete stranger to the helper.  
         
         In 2003, Columbia University sociologist Duncan Watts performed 
        in experiment using email to test large-scale small-word social networks 
        and found that many people were not motivated enough to participate. "The 
        attrition rate tends to be high, and if the attrition rate is high at 
        every step, then essentially you have this exponential decay in your ability 
        to find faraway information," said Kleinberg. "And so you have to start 
        asking about incentive mechanisms."  
         
         The Michigan researchers are showing that it's possible to build 
        small-world navigation techniques into a working system in an interesting 
        way and they are aware of the incentive issues, said Kleinberg. To assess 
        whether the system will work, however, requires a large-scale experiment, 
        he said.  
         
         The researchers are still developing and testing the tool, according 
        to Zhang. They have a stand-alone program and implementation that works 
        as a plug-in for existing instant messaging clients.  
         
         The widespread use of instant messengers in daily life and work 
        environments provides the critical mass of people to make the scheme viable, 
        said Zhang. Ultimately, the software is meant to become a human equivalent 
        of the Google Internet search engine for answers to non-Boolean types 
        of questions, he said.  
         
         The system is also part of a larger research project investigating 
        how information flows influence productivity, said Zhang. As part of that 
        project, the researchers have discovered that social networks make individuals 
        more efficient.  
         
         The researchers analyzed a large data set that included communications 
        flows and surveys of people's perceptions of email and found strong statistical 
        correlations between social network factors and individual output, said 
        Zhang. "Searching information from humans directly is the most traditional 
        way that people seek information," he said. "We should really re-examine 
        the value of this method and try to use new technology to promote it." 
         
         
         Zhang's research colleague was Marshall Van Alstyne. The researchers 
        presented the work at the Association of Computing Machinery (ACM) Computer-Human 
        Interaction (CHI) 2004 in Vienna, Austria April 24 to 29. The research 
        was funded by the National Science Foundation (NSF) and Intel Corporation. 
         
         
        Timeline:  > 2 years  
         Funding:   Corporate; Government  
         TRN Categories:  Databases and Information Retrieval; Internet 
         Story Type:   News  
         Related Elements:  Technical paper, "SWIM: Fostering Social 
        Network Based Information Search," Computer-Human Interaction (CHI) 2004, 
        April 24-29, Vienna, Austria  
         
         
          
      
       
        
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       July 14/21, 2004 
       
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