Paper Reading #25: Twitinfo: aggregating and visualizing microblogs for event exploration

Authors

Adam Marcus, Michael S. Bernstein, Osama Badar, David R. Karger, Samuel Madden, Robert C. Miller

Occupation

Michael S. 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 R. 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 C. 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.

Location

Published in the CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems at NYC

Summary

Hypothesis

twitinfo can provide use for summarizing and searching twitter information in terms of events and trends going on

Methods

twelve participants were selected to use this application to see different aspects of a recent event. This experiment focused on usability feedback. Part two of the experiment involved putting a time limit as the users were given five minutes to research a event using this application and then five minutes to write a report about the findings. At the end the users were interviewed about the system and their responses recorded.

Results

participants were able to recreate a some what detailed information on the events that they researched on. The users tended to perform free form exploration as they focused on the largest peaks and reads the relevant tweets. Afterwards they tended to follow links that were related to the event. The tweets themselves however tended to confirm specific details rather than provide new information. In the second part of the experiment, people tended to skim peak labels to get a sense of time line and people rarely read the outside links for additional information.

Content

The article focuses on this application called twitinfo and the inner workings and details of how it runs. The application itself allows users to classify and look into tweeted information. The paper focuses on how the user interacted with this device and what kind of information people were able to gather using this device.

Discussion

I personally thought the whole application was some what interesting since it can help someone keep track of a certain event by checking information at its peak times. However i believe that it would only be good for merely confirming information like the article said. I do not think that the application itself can have great impact on any actual events.