Social-Networking by wuxiangyu

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									Social Networking Retrieval:
    Wikis, Blogs, RSS, Networks,
     and Social Search Engines
                                         LIBR 557
                                November 26, 2007
                    Amanda McKinlay, Josh Niemier,
                      Jodi Peterson & Lisa Ricciuti
          What is Web 2.0?

 Web 2.0 = ―architecture of participation‖
  (Ziesche) for WWW.
 Users generate and distribute Web content,
  enabled by technical developments as well
  as a culture of freedom to share and re-use
  information (Ziesche).
 Users create, evaluate, and distribute
  information.
     What is Social Networking?
   ―Communities of people who share interests
    and activities, or who are interested in
    exploring the interests and activities of others‖
    (Wikipedia)
   Ever increasing # of:
       Social networking communities (like Facebook)
       Wikis
       Blogs
       Mini-blogs (like Twitter)
       Social bookmarking sites (like Del.ico.us)
       Q&A sites (like Askaway)
       Collaborative harvesters (like Digg)
Social Network Use
                Globally, 1/5 adults
                 visited a social
                 networking site
                Social networkers
                 spend more than 7
                 hrs/week on social
                 networking sites.
                55% of American
                 teenagers creating
                 profiles on social
                 networking sites in
                 2006 (Lenhart).
                48% of these teens
                 visit social networking
                 sites at least daily
                 (Lenhart).
           Social Networking &
          Information Retrieval
Complications:
 Social networking sites=massive arena
 Users make the rules: ―This is the user‘s web now,
  which means it‘s my web and I can make the rules‖
  (Shelley Powers qtd. in Hammond et al)
 Content may change hourly, which is too fast for
  search engines to keep up with (Nishimura).
 Web 2.0 technology, including Flash and AJAX
  (Asynchronous JavaScript and XML), is ―unfriendly‖
  to search engines (Sijjad).
          Social Networking &
         Information Retrieval
Complications:
 Retrieving relevant information from Social
  Networking sites.
   Pages containing multiple topics (Nishimura).
   Ambiguous titles (Nishimura).
   Tagging…
              Social Networks &
            Information Retrieval
   Niche search engines may facilitate the
    retrieval of relevant information from social
    networking sources:
     Wikis
     Blogs
     RSS feeds
     Social Network Communities
     Social Search Engines
                       Tagging
   Descriptive word assigned to a bookmark,
    blog, wiki, web page, etc.
       Usually restricted to one word or combination
        words with punctuation between
 Assigned by the user for personal use
 Used for retrieval, networking and grouping
 Forms a tag cloud – visual representation of
  terms used
                 Tagging Pros
   Allows for additional access points to retrieve
    material
   Free text – though usually confined to only one
    word, or combinations with varied punctuation
   Contemporary and common language/terms –
    more adaptable than other systems like LCSH or
    Dewey
   Helps to create networks and social interactions
               Tagging Cons
   Inconsistent
     Dependent on the creator‘s mood/style
     Word combinations can vary (ex. hongkong OR
      hk OR HK)
 Subjective
 No traditional hierarchical structure to
  information
 Based on the premise that popularity =
  quality
              Libraries and Tags
   Starting to use http://del.icio.us
       Allows sharing and participation between
        patrons, librarians and libraries
   Encourages interaction
       Reaches a different type of patron
 Search terms are available in common
  language
 Provides multiple retrieval options
 Slowly gaining momentum…
         Libraries using del.icio.us*
   Beaufort County Library
    Bibliotheques de l'Universite Paris-Sorbonne
    Colorado State University Pueblo
    Delany Library
    Dublin City Public Libraries and Archives
    Hardin Library for the Health Sciences, University of Iowa
    Health Sciences Library, Stony Brook
    Lansing Public Library
    Maui Community College Library
    McMaster University Libraries
    McMaster University, Emerging Technologies Group
    Menasha Public Library
    Missouri River Regional Library
    Nashville Public Library
    North Metro Technical College
    San Jose Library
    San Mateo Public Library
    Seldovia Public Library
    Springfield Technical and Community College
    Tampa Bay Library Consortium
    Thunder Bay Public Library
    University of Alberta Libraries
    University of Florida George A Smathers Library
    University of Georgia Libraries Cataloging Department
    University of Michigan Dentistry Library
    University of Michigan Health Sciences Libraries
    University of Michigan Library 2.0 program

    *<http://www.libraryjournal.com/article/CA6479377.html> (17 November 2007)
Thunder Bay Public Library (Ont.)




  <http://www.tbpl.ca/internal.asp?id=283&cid=333 > (16 November 2007).
The old fashioned way…
                        New social way…




<http://www.tbpl.ca/internal.asp?id=283&cid=4548 > (16 November 2007).
<http://del.icio.us/TBPL/Aboriginal > (16 November 2007).
<http://del.icio.us/TBPL/Aboriginal > (16 November 2007).
    Ann Arbor District Library, MI
   January 2007 – ―released what developer John
    Blyberg called the SOPAC, or the social library
    catalog.‖*
   Tagging integrated directly into the catalog
   Every patron can tag after creating an account
   Tags are searchable through catalog records and
    in a catalog-wide tag cloud* with the 500 most
    popular ones

    * Rethlefsen, Melissa L. ―Tags Help Make Libraries Del.icio.us.‖ Library
    Journal (15 Sept. 2007) : 26.
<http://www.aadl.org/catalog > (16 November 2007).
                                   Wikis

 ―a type of computer software that allows
  users to easily create, edit and link web
  pages.‖*
 Usually a collaborative effort
 Way to organize and disseminate information
  among many users

    *Wikipedia: The Free Encyclopedia. <http://en.wikipedia.org/wiki/Wiki > (17
    November 2007).
                          Wiki Pros
   Easy to use and accessible
   Way to share information and collaborate
       Everybody can participate
   Keeps a record and an edit history automatically
       Version control
   Email notifications of updates are available
   Can be kept public or made private
   Some wikis offer a tagging option
       For internal organization and retrieval
                   Wiki Cons

   Everybody has access to it
     Challenges credibility
     Potentially open to spammers

   Difficult to search
     No index
     Non-existent access points

 May not be used, or used incorrectly
 Maintenance
    Wiki…as a social networking
          retrieval tool
 Starting to be used for Intranets and
  Knowledge Management
 Centralized place to update and store
  information
 Accessible anywhere the web is available
 Can cater to specific or broad interests
            Libraries and Wikis

 Outreach
 Encourages participation/discussion
     Patrons
     Staff/Librarians

 Internal organization and information
  dissemination
 Used for librarians, book discussions, subject
  resource pages…
 The Council of Prairie and Pacific
  University Libraries (COPPUL)
 Designed a wiki to reach other librarians
 Tutorial information centre project
 ANimated Tutorial Sharing Project (ANTS)
 Librarians can add, download, use, share
  tutorials to stay up to date
 ―repository for all kinds of library related
  learning objects‖*

*<http://ants.wetpaint.com/ > (20 November 2007)
<http://ants.wetpaint.com/> (20 November 2007)
                            ANTS DSpace




< http://ants.wetpaint.com/page/Uploading+and+Downloading+Tutorials > (22 Nov 2007)
Simple search on ANTS
           St. Joseph County
           Public Library (IN)
 Use a wiki for subject guide
 Each topic links to a separate wiki page
 Discussion tab for patrons
 Librarian only section
 Anybody can view it and add to discussion,
  but not content
 Gives librarians ―control‖ over their sections
―Subject Guides.‖ St. Joseph County Public Library (IN)
(I<http://www.libraryforlife.org/subjectguides/index.php/Main_Page > (17 November 2007).
Biography and memoir cont…
        Retrieval tools for Wikipedia:
        wikiseek - www.wikiseek.com
   Restricted to searching Wikipedia
       Sites referenced in it
   ―utilizes a category refinement technique‖*
       Based on user tagging and categorizations
   No search button
       Must select a category (All results = default)
   1st three hits are in Wikipedia
       Denoted by a ―W‖
                    Wikiseek

   Pros
     Offers targeted searches within a specific area
     Supports AND/OR operators
     ―Phrase‖
     Available search extensions
< http://wikiseek.com/tools/index.php > (20 November 2007)
                   Wikiseek

   Cons
     Doesn‘t support ―NOT‖ operator
     No truncation
     No wildcard
     Must search within an assigned category (no
      freedom to choose)
     No way to determine how categories are
      assigned
     Searching partially dependent on user tags
< http://wikiseek.com/?q=bassoon > (20 November 2007)
Searching wikis: www.qwika.com

   Pros
     Search interface specifically for wikis
     Translates wikis in other languages
          12languages so far with direct links to wikis in those
          languages
       Offers searching in other languages
          Uses   other alphabets
       Offers direct links to topics in the news
          Newsadjusts accordingly to each language
          (sometimes)
       Links users to FactBites (not for wikis)
www.qwika.com

   Cons
     Still in beta
     No advanced search option
     Doesn‘t support any operators, truncation,
      wildcard or ―phrase‖ searching
     Currently only searches 1158 wikis
     Information about relevance is sparse and
      mostly non-existent
Simple search on qwika




 <http://www.qwika.com/> (22 November 2007).
Simple search on qwika




 <http://www.qwika.com/find/bassoon> (22 November 2007).
<http://www.qwika.com/find/bassoon > (22 November 2007).
                            Qwika in Greek




<http://www.qwika.com/find-el/ > (22 November 2007).
             Blogs & RSS Feeds:
            What’s the Difference?
 Blogs:
     ―an online diary; a personal chronological log of thoughts published
      on a Web page‖ (Webster‘s New Millennium Dictionary of English)

     ―a personal journal on the Web‖; ―updated frequently‖; ―allow millions
      of people to easily publish their ideas, and millions more to comment
      on them‖ (Technorati)

     Blogs enable social networking by allowing comments, and linking
      between blogs; one blog may also have multiple ―authors‖
             Blogs & RSS Feeds:
            What’s the Difference?
 RSS       feeds:
    A way of accessing frequently updated information; allows the user
     to pull content from many websites to one feed reader

    ―Allows anyone with a website to ‗syndicate‘ their content‖; a way of
     representing part of a blog (or other website) (Technorati)

    Easily see updates without having to visit each site individually
                Why Search Them?

   Why search blogs?
       Current information
       A variety of perspectives
       May cover topics not covered elsewhere
       ―offer access to breaking news, rumors, evaluations and other
        information that might not otherwise readily be available from
        our traditional databases‖ (Notess)


   Why search RSS feeds?
       Current information
       Pull information from blogs & other frequently updated sites
       May include information from newsgroups
                Searching Blogs

   Two types of searches:
     Searching within a blog
     Searching for a blog



   Searching within a blog:
       Most blogs provide the
        option to view archived entries
        chronologically
        (by month or by week)
      Searching Within Blogs

   Some blogs may
    allow keyword
    searches

   Or may use Google
    for internal searching
        Searching Within Blogs

   Tags or ―categories‖ are often used to
    describe each entry; assigned by the author
        Searching Within Blogs

   Reader can then
    browse by
    category/tag
           Searching For Blogs

   There are many blog search engines:
              Blinx                 Fagan Finder
              Blogarama             Fastbuzz
              Blogdigger            Gigablast
              Blogdimension         Icerocket
              BlogPulse             Keotag
              Blogsearchengine      Search4Blogs
                                     Sphere
              BlogUniverse
                                     Technorati
              Bloogz                Waypath
             But why use specialized
                 search engines?
   According to Nishimura (UBC Library page):
        Most regular search engines only index webpages every few
         weeks, while blogs and RSS feeds may be updated daily
         or even many times a day

        Each page of a blog will often contain information on many
         topics, making it hard for the search engine to identify the topic

        Blog authors rarely provide metadata (but as we‘ve learned,
         many search engines ignore meta-tags because they can
         be misleading)

        Blogs tend to have ―unhelpful‖ titles that do not clearly describe
         their content (for example, ―The Blog Driver‘s Waltz‖ primarily
         features information on technology, digital initiatives and libraries)
          How are specialized
     blog search engines different?
   Refresh index more often (once or more a day)

   Many blog search engines have a date-specific
    search capability (Thelwall & Hasler)

   Blog search engines are specially designed to take
    advantage of blog structures & formats, so they can index
    individual postings (Thelwall & Hasler)
       However this is only true of common blog formats
        – more about this when we get to RSS
Example: Technorati
    http://technorati.com
“Popular”
“Topics”
Sample Search
Results
Revised Search
Results
        Searching For RSS Feeds

   There are many RSS feed search engines:

       2RSS
       Bloglines
       Fagan Finder
       NewsIsFree
       Search4RSS
       Syndic8.com
        Searching For RSS Feeds

   There are also many, many RSS feed search engines
    that are not currently working!

       Feedster (message up saying it is currently ―changing‖)
       Daypop (―problem loading page‖)
       Complete RSS (―problem loading page‖)
       EasyRSS (―problem loading page‖)
       Edu_RSS (―This script isn‘t functioning right now.‖)
       Fyuze (―problem loading page‖)
       Bulkfeeds (―problem loading page‖)
       Feedback (502 Bad Gateway)
      How are specialized RSS feed
       search engines different?
   Like blog search engines, they refresh their indexes
    more often
     ―Feed aggregators query a site about every hour‖ (Pikas)


   RSS format is more easy to index so even a blog uses an
    unusual format can be indexed if it also has an RSS feed
    (Thelwall & Hasler)

   They index individual items rather than pages that might
    contain many items
Example: Bloglines
    www.bloglines.com
                      Search

Simple   Search or Advanced Search
Sample Search
No Results!
Revised Search
        Searching Library Blogs
                     http://liszen.com

   Uses Google Custom Search to search
    over 750 library blogs
         Searching Library Blogs
                         http://liszen.com

   Plus option to refine results:




   But because it‘s using Google instead of a specialized
    search engine, results go to overall site, not specific entries
   And it still has the problem with less frequent indexing
    Searching Social Networks

 Searching social networks like Myspace,
  Friendster, Linkedin, Facebook, etc.
 Crawling the network
 Social Network Search sites Wink, Zoominfo,
  Rapleaf and Spock
     Profile for your Profiles?

 Profile aggregator‘s
 Maintains your online reputation
 The Ultimate profile?
 Wink Launched in November 2006, and
  since then has acquired 250 million profiles
 They have just recently partnered with
  Zoominfo.com, another social search engine
  that specializes in people and employer
  profiles to aquire 38 million more profiles
 Their goal is to eventually index every person
  on Earth
Front Page
                           Wink.com

   Wink is a search engine designed to find people and
    employs user participation in an attempt to provide
    better results
       the user participation it employs includes tagging, rating,
        and sharing
   It crawls many social network sites to collect
    information on users
       Sites crawled include MySpace, Hi5, LinkedIn, Friendster,
        Bebo, Live Spaces, Xanga, Twitter
                    Searching Wink

   The search interface is fairly simple
       The main thing used to search is simply someone‘s name
        or user name
       You can also refine the search using limiters like interests,
        location, schools, groups, career, and tags
       You can also search these limiters to find people with like
        interests
       You can also browse people by name
       Wink automatically employs Boolean and, but does not
        support OR, nor does it allow truncation
   The results page also includes hits from Google
    underneath the hits from Wink
Wink: Josh Niemier
Wink: Josh Niemier
Wink: Josh Niemier
Wink: Josh Niemier
Wink Widget
                   Problems

   Searching by name was unsuccessful
   Where the information comes from
   Privacy
Spock
                       Spock

   Spock is another people search engine that gathers
    most of its data from Social Networks
   It is still in Beta
   ―Astonishing! Spock thinks you are a pedophile‖
                          Problems

   It‘s easy to be misrepresented
   You must claim your profile to vote down tags
   You cannot make the profile private or limit who has
    access to it
   Mad Libs example
       ―Joe Z. is a man-whore who hangs out and stranger‘s
        houses and drinks rum and cokes (Tynan, 2007)‖
   Jason Aravosis and the Mark Foley Case
Rapleaf and Upscoop
                Rapleaf and Upscoop

   Privately owned startup consisting of two consumer websites
   Upscoop allows people to search for people using their email
   The emails are collected to use in Rapleaf
   50,000,000 emails
   Same company owns a third company called TrustFuse, which sells data but
    not email addresses
   They manipulate Social Network‘s own search engines to get member
    emails when possible, and use a ―special sauce‖ for others
   Olsen, 2007
          Social Search Engines
   ―Social search tools are internet wayfinding services
    informed by human judgment. Wayfinding, because
    they‘re not strictly search engines in the sense that
    most people know them. And human judgment means
    that at least one, but more likely dozens, hundreds or
    more people have ‗consumed‘ the content and have
    decided it‘s worthy enough to recommend to others.‖
    (Sherman)
   Collaborative filtering: ―method of making automatic
    predictions (filtering) about the interests of a user by
    collecting taste information from many users
    (collaborating)‖ (Wikipedia).
   Philosophy: your friends or like-minded people know
    best what kind of resources you‘re interested in.
           Social Search Engines

   The idea is not entirely new:
       Yahoo‘s Directory, About.com etc. filter web
        sources through human judgment.
   Difference = social search engines make use
    of human intelligence (through shared
    bookmarks, tagging of content, voting) in
    combination with computer algorithms
    (Sherman).
    Types of Social Search Engines:

   Search engines are exploring the concept of
    social searching from different angles.
     Personalized search engines
     Collaborative directories
     Collaborative harvesters
     Question-and-Answer directories
    Personalized Search Engines

 create a specialized search engine focusing
  on a narrow topic.
 Theory= people passionate about a subject
  will create a collection of quality resources
  that other searchers can benefit from.
     Rollyo.com
     Eurekster.com
Personalized Search Engines:
           Rollyo
               Create your own
                ―Searchroll‖ by including
                only sites (up to 25) that
                you‘re interested in
                searching.
               Search & edit other
                people‘s Searchrolls
              No Boolean
                operators,proximity,
                stemming, exact phrase
                search
              Easy to create through
                step-by-step instructions
      Personalized Search Engines:
                Eurekster
   Create your own ―Swicki‖
   Search results= from your
    choices & web/blogs.
   Community = people
    interested in the subject of
    your swiki.
   People in your community
    alter your search engine‘s
    results by tagging, voting,
    submitting urls.
   Eurekster monitors users‘
    search patterns
   More use = higher
    relevancy
     Personalized Search Engines:
               Eurekster
   Buzzcloud=
    ―hot‖ terms
   Owner
    manages tags
   Customize look
    and feel
   ―Grab‖ it and put
    it on your
    website
     Personalized Search Engines:
               Eurekster
 Supports AND logic, exact
  phrase searching, stemming
 Creators must carefully conceive
  of keywords in ―training‖ their
  swikis—there‘s potential for the
  keyword filter to be useless or
  too restricting.
 The swiki has to be USED for it
  to become USEFUL
 Not a lot of voting
 Web results=too obvious ex)
  Wikipedia & Amazon
 Good idea—could be useful if a
  true community used Eurekster
  instead of Google.
     Collaborative Directories

 User-generated content sites; rely on users
  to submit their favourite links and create the
  site‘s index.
 Theory: users will save time by searching
  collaborative directories, since all the useless
  info has already been weeded out by
  previous searchers.
Collaborative Directories:
        Prefound
                  Register and
                   begin to collect
                   ―great links.‖
                  Name 3 interests,
                   qualifying each
                   interest by
                   increasingly
                   narrow keywords
                   so that your
                   searches can be
                   customized to
                   your interests
                 Interest=max. 8
                   characters
Collaborative Directories:
        Prefound
                    Download an
                     application
                     (Windows only) so
                     that from your
                     computer‘s
                     bookmarks tab,
                     you can bookmark
                     a site to
                     Prefound.com…if
                     you‘re logged in.
Collaborative Directories:
        Prefound
                  Searching
                   doesn‘t require
                   registration
                  Advanced search
                   = Boolean
                   operators and
                   exact phrase
                  Searching
                   requires more
                   thought than
                   larger search
                   engines.
       Collaborative Directories:
               Prefound




Significant browsing
Poor participation
Confusing and time consuming
# of ―found‖ sites of general interest must be limited
Potential to hit gold
     Collaborative Harvesters

 ―tap into the collective wisdom of their users‖
  (Sherman)
 Users post found sites, then people vote on
  the site‘s interest to them
 A lot of votes=content becomes a visibly
  recommended site for the rest of the
  community. (Sherman)
 Popular collaborative harvesters= Flickr,
  YouTube, Digg (news/media harvester)
             Collaborative Harvesters:
                     Sproose
   Like a regular search engine,
    except hits ranked by votes.
   Logic = ―Only a quality site
    reviewed by real people can
    move up.‖
   Registration =
        You influence relevance ranking
        Sproose remembers sites you
         vote for
        Post comments about sites
        Tag sites
        Share your search history…akin
         to the pearl-growing search
         strategy
   Search solely within sites that
    have been voted for.
        Collaborative Harvesters:
                Sproose
―REAL people share the
 rakings on Sproose—
 leading to REAL results‖
Quality is subjective and
 dependent upon levels of
 expertise
Don‘t need to download
 any applications
Spelling suggestions
AND/OR logic
Exact phrase search
User-friendly, intuitive,
 familiar interface
Q&A Directories:
    Hakia
           ―Meet Others‖: meet people who
            are searching the same thing
            that you are.
           Users post messages to one
            another--anonymously by
            default.
           Purpose?
              Buy and Sell?
              First-hand info? (ex: health)
           The top 5 search rooms
            (18/11/07):
              Cancer
              New York real estate
              Search Engines
              Does Airborne immune
                booster really work?
              San Francisco Computers
Q&A Directories:
    Hakia
        Search for something
         that does not exist on
         WWW
        Spamming
        Duplicate advertising
        Maybe nobody will
         bother to answer you.
           Social Search Engines:
                 Evaluation
EFFORT!
     Who is sending their queries out across the Internet,
      forming ‘groups’ and ‘circles,’ ‘crowds’ and
      ‘communities?’ Who is stopping to vote on every web
      page they land on? And who’s sharing their bookmarks
      and favorites, or, even more mysteriously, checking out
      other peoples’? But to chat with other searchers, or IM
      them, poke, Skype or Twitter them? Who’s doing all of
      this social networking, who’s got time for that much extra
      work and that many interruptions? (Searching)
     Effort to educate oneself about each new kind of social
      search engine
     Effort to register
        Social Search Engines:
              Evaluation
Web‘s too big for human minds to try to control
 (Sherman)
Tag words are ambiguous, chaotic, messy
 (Sherman)
Spammers can skew results (effort‘s required to
 delete spam)
Small community may influence popularity of sites
―Some ‗informed‘ influences on search results
 come from egregiously uninformed people and
 downright idiots‖ (Sherman)
        Social Search Engines:
              Evaluation
May work well for subjective queries… like
 seeking a good regional restaurant or tourist
 attraction (Mills)
―Information that … only a flesh and blood
 person can provide‖ (Searching)
If the concept catches on, then mass
 collaboration and voting of results should, in
 theory, refine relevant results.
              Conclusion

 Social networking will continue to influence
  search engines and information retrieval.
 ―If you‘re looking for a unique perspective
  and perhaps some information you won‘t find
  anywhere else, don‘t overlook social
  networking sites‖ (Fox).
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