Humanity Road Inc. uses TweetTracker to monitor emerging disasters, and Quicknets partnered with us to test their system in a disaster simulation game on the Arizona State University Campus.
ARTIS Research and University of Michigan used data collected through TweetTracker to analyze the factors responsible for Arab Spring, and Carnegie Mellon University and the School of Social Transformation at ASU use TweetTracker for their research as well.
TweetTracker has analyzed over 130,000,000 tweets!
Step 1. Track
TweetTracker collects tweets according to hash tags, search terms, and location, allowing you to filter through billions of posts to Twitter in real-time. Select an event below to see a live feed of tweets on the map.
Step 2. Analyze
TweetTracker allows you to compare activity across different hash tags, search terms, and locations.
Step 3. Understand
TweetTracker provides visualizations across a variety of metrics that can bring light to important trends.
Demo: Tweet Maps
To the right, you can see a demonstration of one of TweetTracker's most powerful features: the ability to visualize tweets in real-time on a map that leverages geotagging and profile locations.
Record, Rewind, and Replay!
TweetTracker lets you record events, go back in time, and replay them as they occurred on Twitter. TweetTracker opens up new opportunities to understand the cause and development of different events in real-time.
How does it work?
TweetTracker collects the tweet ID, username, time, location, tweet text, hashtags, urls, other users mentioned, and replies for every tweet it tracks. The system also allows a variety of visualizations based on this information, including streaming geospatial maps, tag cloud summarizations, post-event investigations in pseudo real-time, automatic translation of Non-English tweets, and keyword trending and comparison.
- Shamanth Kumar, Fred Morstatter, and Huan Liu. "Twitter Data Analytics", Springer 2013
- Fred Morstatter, Shamanth Kumar, Huan Liu, and Ross Maciejewski. "Understanding Twitter Data with TweetXplorer"(Demo), KDD 2013
- Shamanth Kumar, Geoffrey Barbier, Mohammad Ali Abbasi, and Huan Liu. "TweetTracker: An Analysis Tool for Humanitarian and Disaster Relief"(Demo), ICWSM 2011
TweetTracker is built at the Data Mining and Machine Learning Lab at Arizona State University.
Contact Us: firstname.lastname@example.org | (480) 727-7349 | 699 S. Mill Ave. Suite 501, Tempe, AZ 85281
This project is funded by the Office of Naval Research.