semantic twitter analyzing tweets for real time event notification
DESCRIPTION
TRANSCRIPT
SEMANTIC TWITTER: ANALYZING TWEETS FOR
REAL-TIME EVENT NOTIFICATION
Makoto Okazaki and Yutaka Matsuo
The University of Tokyo
Popular microblogging service Short message within 140 characters Real-time nature
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)
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
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
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
The concept of system
Mass media Advanced social mediumSocial media
Mass media
UserInformation
Semantictechnology
Real-timeliness: lowUsefulness: high
Real-timeliness: highUsefulness: low
Real-timeliness: highUsefulness: high
Useful information
Un-useful information
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.
Earthquake information system
shook!
Distance from the earthquake center
Our System
tweetE-mail
Earthquake center
Twitter search API
Mecab
SVMDB
FetcherOur system
User
Sender
Queries Tweets
Text Analyzer
UserUser User …
Detect tweets about the target event
System architecture
“Earthquake”“Shakes”
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
Features
Group A: simple statistical featuresThe 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 featuresThe words before and after the query word
Performance of classificationFeature Accuracy Recall Precision F-value
A 95.00 87.50 63.64 0.74
B 88.00 87.50 38.89 0.54
C 94.00 50.00 66.67 0.57
All 95.00 87.50 63.64 0.74
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 Group C: context word features
he words before and after the query word
Twitter search API
Mecab
SVMDB
FetcherOur system
User
Sender
Queries Tweets
Text Analyzer
UserUser User …
Detect tweets about the target event
System architecture
“Earthquake”“Shakes”
Registration
The detection of the past earthquakes
Facts about earthquake detection
Date Magnitude
Location Time First tweetdetected
#Tweets Announce of JMA
Aug 18 4.5 Tochigi 06:58:55 07:00:30 35 07:08
Aug18 3.1 Suruga-wan 19:22:48 19:23:14 17 19:28
Aug 21 4.1 Chiba 08:51:16 08:51:35 52 08:56
Aug 25 4.3 Urakawa-oki 02:22:49 02:23:21 23 02:27
Aug 25 3.5 Fukushima 22:21:16 22:22:29 13 22:26
Aug 27 3.9 Wakayama 17:47:30 17:48:11 16 17:53
Aug 27 2.8 Suruga-wan 20:26:23 20:26:45 14 20:31
Aug 31 4.5 Fukushima 00:45:54 00:46:24 32 00:51
Sep 2 3.3 Suruga-wan 13:04:45 13:05:04 18 13:10
Sep 2 3.6 Bungo-suido 17:37:53 17:38:27 3 17:43
The number of tweets on earthquakes
08/08 0008/08 1808/09 1208/10 0608/11 0008/11 1808/12 1208/13 0608/14 0008/14 1808/15 1208/16 0608/17 0008/17 180
20
40
60
80
100
120
140
160
Nu
mb
er o
f tw
eets
The location is obtained by a registered location on the user profile on twitter.
Dear Alice,
We have just detected an earthquakearound Chiba. Please take care.
Best,
Toretter Alert System
Another prototype
Rainbow informationUsing a similar approach used for detecting
earthquakes.Not so time-sensitiveRainbows can be found in various regions
simultaneouslyWorld rainbow mapNo agency is reporting rainbow information
Another plan
Reporting sighting of celebritiesMap of celebrities found in citiesWe specifically examine the potential uses
of the technology. Of course, we should be careful about privacy issues
Related works
TweettronicsAnalysis of tweets about brands and
products for marketing purposes Web2express Digest
Auto-discovering information from twitter streaming data to find real-time interesting conversations
Conclusion
Earthquake prediction system
The system might be designated as semantic twitter
Twitter enable us to develop an advanced social medium
Thank you