55 days left

Chapter 6

I'm a bit stuck on how to progress with the chapter. I've completed everything to justify and describe the development of the algorithm. Within that I've presented the numbers on accuracy. I'm not sure what to do next - do I have to implement these other algorithms and do a comparison? Can I just wrap it up and show how it applies? I'm not convinced that it is a significant enough contribution to just present the algorithm and give it's actual accuracy. I have to show an improvement or something. Because I don't have a clear plan, I was not able to make any real progress here today.

Chapter 8: TrustMail

I figured out that the analysis I want to do on this is to compare how many messages are caught with a close social network filter and how many are caught with an extended social network filter. I am going to use the enron email repository for this, and I downloaded that (150 users, about 5GB of messages) tonight. Those 150 users are the enron employees, but there should be many more *total* users because the employees received and sent email to people outside the company. Hopefully the social network there won't be too dense. If I can show that with an extended social network that a greater percentage of messages are caught, then the analysis from chapter 6 will lead to a reasonable conclusion that that percentage of messages will also be rated accurately enough to give the user a benefit.

The obvious next step will be to extract the social network from these messages, into a *much* smaller data set.

Both FilmTrust and TrustMail rely on the assumption that sorting what the user sees according to trust rating is a good thing. I need to prove that somewhere. Since I am not conducting a user study on TrustMail, I will ahve to devise a test to administer to FilmTrust users to see if they see a benefit from having the reviews with higher ratings appear more prominently.