Semantic Twitter Analyzing Tweets For Real Time Event Notification
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  • 1. Semantic Twitter:Analyzing Tweets for Real-time Event Notification
    Makoto Okazaki and Yutaka Matsuo
    The University of Tokyo
  • 2. Twitter
    Popular microblogging service
    Short message within 140 characters
    Real-time nature
  • 3. Studies on Twitter
    Why we twitter: Understanding microblogging usage and communities(Java et al. 2007)
    Analysis indicators for communities on microblogging platforms(Grosseck et al. 2009)
    Microblogging for language learning(Borau et al. 2009)
    Microblogging: A semantic and distributed approach(Passant et al. 2008)
  • 4. Work on Semantic Web
    How to integrate linked data on the web
    Automatic extraction of semantic data
    Extracting relation among entities from web pages
    Extracting events
  • 5. Idea
    Means of integrating semantic processing and the real-time nature of Twitter have not been well studied
    Combining these two directions, we can make various algorithms to process twitter data semantically
  • 6. Proposal
    Tweet delivery system
    Delivering some tweets if they are semantically relevant to users’ information need
    Example: earthquake, rainbow, traffic jam
    Earthquake prediction system targeting on Japanese tweets
  • 7. The concept of system
    Useful information
    Un-useful information
    Mass media
    Semantic
    technology
    Information
    User
    Real-timeliness: low
    Real-timeliness: high
    Real-timeliness: high
    Usefulness: high
    Usefulness: low
    Usefulness: high
    Mass media
    Advanced social medium
    Social media
  • 8. Earthquake information
    Lots of earthquakes in Japan.
    Earthquake information is much more valuable if given in real time.
    Japanese government has allocated a considerable amount of its budget.
    Gathering information about earthquakes from twitter.
  • 9. Earthquake information system
    Our System
    tweet
    E-mail
    shook!
    Distance from the earthquake center
    Earthquake center
  • 10. System architecture
    Twitter search API
    Queries
    Tweets
    “Earthquake”
    “Shakes”
    Our system
    Fetcher
    Text Analyzer
    DB
    Mecab
    SVM
    Detect tweets about the target event
    Sender
    E-mail
    User
    User

    User
    User
  • 11. Classification
    Clarifying that tweet is really referring to an actual earthquake occurring
    Classifier using support vector machine(SVM)
    Preparing 597 examples as a training set
  • 12. Features
    Group A: simple statistical features
    The number of words in a tweet, and the position of the query word in a tweet
    Group B: keyword features
    The words in a tweet.
    The number of each words in a tweet.
    Group C: context word features
    The words before and after the query word
  • 13. Performance of classification
    • Group A: simple statistical features
    • 14. the number of words in a tweet, and the position of the query word in a tweet
    • 15. Group B: keyword features
    • 16. the words in a tweet
    • 17. Group C: context word features
    • 18. he words before and after the query word
  • System architecture
    Twitter search API
    Queries
    Tweets
    “Earthquake”
    “Shakes”
    Our system
    Fetcher
    Text Analyzer
    DB
    Mecab
    SVM
    Detect tweets about the target event
    Sender
    E-mail
    User
    User

    User
    User
  • 19. Registration
    The detection of the past earthquakes
  • 20. Facts about earthquake detection
  • 21. The number of tweets on earthquakes
  • 22. E-mail
    The location is obtained by a registered location on the user profile on twitter.
    Dear Alice,
    We have just detected an earthquake
    around Chiba. Please take care.
    Best,
    Toretter Alert System
  • 23. Another prototype
    Rainbow information
    Using a similar approach used for detecting earthquakes.
    Not so time-sensitive
    Rainbows can be found in various regions simultaneously
    World rainbow map
    No agency is reporting rainbow information
  • 24. Another plan
    Reporting sighting of celebrities
    Map of celebrities found in cities
    We specifically examine the potential uses of the technology. Of course, we should be careful about privacy issues
  • 25. Related works
    Tweettronics
    Analysis of tweets about brands and products for marketing purposes
    Web2express Digest
    Auto-discovering information from twitter streaming data to find real-time interesting conversations
  • 26. Conclusion
    Earthquake prediction system
    The system might be designated as semantic twitter
    Twitter enable us to develop an advanced social medium
  • 27. Thank you