Paper Reading #25: TwitInfo: Aggregating and Visualizing Microblogs For Event Exploration

• Title: TwitInfo: Aggregating and Visualizing Microblogs For Event Exploration
• Reference Information:
• Adam Marcus, Michael S. Bernstein, Osama Badar, David R. Karger, Samuel Madden, and Robert C. Miller. 2011. Twitinfo: aggregating and visualizing microblogs for event exploration.  In <em>Proceedings of the 2011 annual conference on Human factors in computing systems</em> (CHI '11). ACM, New York, NY, USA,  227-236. DOI=10.1145/1978942.1978975 http://doi.acm.org/10.1145/1978942.1978975
• UIST 2010 New York, New York.
• Author Bios:
• Adam Marcus is a graduate student at MIT.  He received his undergraduate degree from Rensselaer Plytechnic Institute.
• Michael S. Bernstein researches crowdsourcing and social computing.  He is in his final year at MIT.
• Osama Badar is a graduate student at MIT.
• David R. Karger is a member of the AI laboratory at MIT.  He has spent time working for Google.
• Samuel Madden is an associate professor at MIT.  Has developed systems for interacting with mTurk.
• Robert C. Miller is affiliated with Carnegie Mellon University.  He has 71 publications in the ACM over the last 15 years.
• Summary
• Hypothesis:
• The researchers hypothesize that information aggregated from microblog sources, Twitter in particular, can be used to study events.  This should be accomplished in real time and produced by a system that makes data visualization and exploration simple and intuitive.
• Methods
• Researchers developed a tool called 'TwitInfo' to implement the goals set forth in their hypothesis.  They then evaluated the effectiveness of their system by letting average users of twitter and an award winning journalist test it.
• Results
•  The evaluation showed that TwitInfo effectively analyzed events based on spikes in tweets and allowed users to easily gain a shallow understanding of a chain of events.  The journalist emphasized that this knowledge was only shallow, but that the tool still allows people to gather an understanding of events from the first person point of view as they unfold.
• Contents
• The paper presents a tool that is able to analyze twitter information that is not domain specific in real time which has not been effectively accomplished before.  The major limitations of this system are that not all interesting events are flagged when analyzing peaks in the number of tweets (such as a yellow card in a soccer game) and that the information available is generally more shallow than what a standard news report would generate.  
• Discussion
• The researchers were certainly able to create a tool that performs the intended functionality.  It is interesting that this article was mentioned since Dr. Caverlee just recently gave a speech to UPE about a project involving Twitter.  Datamining this expansive source of information can certainly produce some interesting results if it can be done correctly.  I'm actually a little surprised that Twitter itself doesn't do more to support such functionality.



Picture Source: "TwitInfo: Aggregating and Visualizing Microblogs For Event Exploration"