Blog #25: TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration

Paper Title: TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration

Authors: Adam Marcus, Michael S. Bernstein, Osama Badar, David Karger, Samuel Madden and Robert Miller

Author Bios:

Adam Marcus

Michael Bernstein: is a graduate student focusing on human-computer interaction at MIT in the CSAIL. His research is on crowd-powered interfaces: interactive systems that embed human knowledge and activity. 

Osama Badar: is currently a member of the CSAIL at MIT

David Karger: is a member of the CSAIL in the EECS department at MIT. He is interested in information retrieval and analysis of algorithms.

Samuel Madden: is currently an associate professor in the EECS department at MIT. His primary research is in database systems.

Robert Miller: is an associate professor in the EECS department at MIT and leads the User Interface Design Group. His research interests include web automation and customization, automated text editing, end-user programming, usable security and other issues in HCI

Presentation Venue: CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems that took place at New York (ACM)

Summary:
Hypothesis: Twitinfo can provide a useful tool for summarizing and searching twitter for information about events and trends.

How the hypothesis was tested: The authors asked 12 participants to use Twitinfo to research different aspects of a recent event. During this part of the process they gathered usability feedback and observed which interface objects were useful or ignored. The second part of the testing involved adding a time limit. Participants were given 5 minutes to research the event using Twitinfo and then 5 minutes to compose a report about their findings. At the end of the session, the participants were interviewed about their reactions to the Twitingo system.

Results: The authors found that participants were able to reconstruct reasonably detailed information about events even without prior knowledge of it. They found that when users were performing the freedom exploration they tended to explore the largest peak thoroughly and read tweets completely. They also drilled in on the map and followed links to related articles. Most of the tweets were only used to confirm event details rather than general the information. When the time constraint was introduced, the focus shifted to skimming peak labels for a broad sense of the event a chronology, and a few people honed in on only one or two links to outside news sources to minimize time spent searching through repeated information.

Discussion:
Effectiveness: I found this a great okay. Although the authors were successful in creating their product, it didn't seem as useful as they thought it would be. It might potentially be useful in a smaller group setting, perhaps if a high school student wanted to read some first-hand posts about an event that occured in school.