Project: Gmail Viz

GmailViz is the project aimed at providing way to analyze your inbox using paramters like 

• last reply to a mail
• importance based on frequency of mail
• user importance in your inbox
• average response rate
• user importance
• timeline of the mail -how frequently you reply and how often you receive the mails from certain senders.

We have used Java Servlets to talk to our database which is in built in oracle. We query the database generate the result and pass it as json viz ajax calls to javascript.

We analyze your inbox such that we find importance of each mail and present to you in graphical form. We also carry out other useful analysis like email overload- suggesting you the mails that ought to be deleted from your inbox because they have not been either replied to in a very long time or their importance in very close. We visualize such emails in form of a scatter chart and present you with the link to those mails such that you can go ahead and delete such mails thereby releasing free space in your mailbox.

We run a batch process to populate tables in our database. Once this batch process is completed by clicking on analyze button on home page which looks like figure shown below you can start analyzing your inbox -

index page for GmailViz

The following are some other screenshots from the vizualization that we do based on analysis of your inbox  -

Chart showing timeline vs importance

Drill down from previous chart zoom-in on particular time period and giving granular details about importance

Email Overload with mail preview

Graph showing when was the user last replied

Graph showing keyword analysis

User importance in your inbox

We used Raphael js and Google Chart API for plotting the chart. The pages were developed using HTML5, CSS3 and Javascript.

Details:

Screencast: http://youtu.be/OdezjHWRM70
SourceCode: https://github.com/NCSUWebViz/Gmail
Site: http://csc591-gmailviz.csc.ncsu.edu:8080/GmailViz/
Data: We build our own dataset by the analyzing mail from your inbox

Team: Sarvesh Pai, Girish Pandit, Nidhi Pathak, Vartika Singh

Thanks to Prof. Dr Watson who provided us vital feedback at various stage of our project.
Also special thanks to Clayton Coleman, Bill Houghteling, and Prof. Patrick Fitzgerald for their valuable insight into our project during demo.