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

References

Adam Marcus, Michael S. Bernstein, Osama Badar, David R. Karger, Samuel Madden, Robert C. Miller.  "TwitInfo: Aggregating and Visualizing Microblogs For Event Exploration". UIST '11 Proceedings of the 23rd annual ACM symposium on User interface software and technology.  ACM New York, NY, USA ©2011.

 Author Bios

Adam Marcus is a graduate student at MIT. He received his bachelor's from Rensselaer Plytechnic Institute.

Michael S. Bernstein research interests lie in social computing and crowdsourcing.

Osama Badar is a graduate student at MIT.

David R. Karger used to work for Google, and is now a part of the AI lab at MIT.

Samuel Madden is an associate professor at MIT. He has worked on systems for mTurk.

Robert C. Miller is an associate professor at MIT. He currently leads the User Interface Design Group.

Summary 

• Hypothesis - A study of massive amounts of microblogs can provide accurate feedback on major events in real time, in this case Twitter.
• Method -The researchers developed TwitInfo, which analyzes all posts with specific tags. These tags are set for an event, such as a World Cup Game. They developed a user interface that was intuitive for users and analyzed events in real time. They then evaluated the usefulness by letting average users test it, as well as a major journalist.
• Results - The results were favorable. The evaluation showed that TwitInfo was accurately able to predict when events occurred. It was also able to analyze on a basic level people's reactions to that event. For example, during a World Cup game, it was able to localize where people were generally happy or generally unhappy towards certain events, such as goals. The journalist maintained that this knowledge was too shallow to rely on alone, but that it was a useful tool to gain a basic understanding at a higher level.
• Content - The paper presented a tool for analyzing Twitter information to gain accurate data on world events. It was able to do so rather successfully, and users generally gave positive feedback. The limitations on this system was that it was not able to show all of the major events, such as a yellow card in the World Cup game, and that the information gathered is too shallow to use as a sole source of data.

 Discussion

This tool impressed me. I rather liked how it was developed, and it was pretty fun to look at the UI (while it was still up and working). I liked how it was able to analyze the massive amounts of data in real time. The sentiment calculation left something to be desired, but such is our current technology. I particularly liked the World Cup game, as it was interesting to see which events were portrayed accurately and what went undetected.