[Mailman-Developers] [GSoC 2012] Metrics

[Patrick Ben Koetter]

George,

let me throw in some thoughts just to annoy you ;)

Like with most statistical data I mostly see the figures being used to give
statements on quantity - top poster, number of threads etc. Do you think it
would be possible to also make some statements on quality?

Let me give an example: Mailing lists are often places where people go to ask
for advice. Someone asking usually starts a thread and continually keeps
replying. That easily makes a person top poster and might make the same person
a thread starter, but number of posts and threads started gives no indication
of that persons knowledge (concerning the mailing lists topic).

OTOH someone who has been on the list for ages, who replies more often than
starting threads and who ends threads often after she has replied might very
well be a very knowledgeable person, because she gives the one answer that
solves the problem.

Do you think it would be possible to deduct such quality oriented statements?

p at rick

P.S.
Do you also plan to deliver a tool that analyzes a mailing list archive in
order to gather your statistical data? Having the statistical data might be a
good reason for people to upgrade their MMx installation to MM3.

* George Chatzisofroniou <sophron at latthi.com>:
> The following document is the lowest level of my design concept. You
> may also read it in my blog [1]. Of course, comments are very welcome.
> 
> --
> Models
> 
> In order to store statistical data, the app will use some Django models:
> 
> Author
> 
> This model represents an author of the mailing list. It mostly keeps
> track of the number of postings and number of threads started.  It has
> the following fields:
> 
> - authorid – IntegerField
> - authormail – CharField
> - totalmails – IntegerField
> - totalthreads – IntegerField
> - firstmsgdate – DateTimeField
> - lastmsgdate – DateTimeField
> 
> MailingList
> 
> This model  counts  the total number of postings and threads started.
> 
> - totalmails – IntegerField
> - totalthreads – IntegerField
> 
> Month
> 
> This model associates the author and the mailing list with each month.
> 
> - author – ForeignKey
> - month – CharField
> - postscount – IntegerField
> - threadscount – IntegerField
> - mailinglist – Boolean (if this is true it corresponds to the whole
> mailing list)
> 
> Year
> 
> This model is similar to month. It has a year field instead of a month field.
> 
> Views
> 
> To display the metrics the Django template system will be used. To
> output the charts i will create some custom tags. The three following
> views will be used:
> 
> - General page – On top, there will be general metrics about total
> authors, total mails and total threads and below three charts (AJAX
> based) that represent number of posts per author, number of threads
> per author and mailing list’s yearly usage. Even below there will be a
> number of charts (equal to the number of years of list’s existence)
> that output monthly usage. At the end, there will be tabular data
> representing the authors of the mailing list along with their number
> of posts, number of threads started and the date of their last post.
> The user will be able to order the tabular data (alphabetically,
> ascending/descending on number of posts, number of threads, date of
> last message) by clicking on the table’s headings (Mail, Mails Sent,
> Threads Started, Last Message).
> 
> - Author page – Each user will have his own page with his own metrics.
> On top, there will be the email of the author, number of posts, number
> of threads started and the dates of first and last message. Below
> there will be monthly usage charts for each year the user is
> subscribed to the mailing list.
> Django Admin page – A ‘Generate’ button will be added to the Django admin page.
> Settings
> 
> The Django app should handle the following configuration parameters:
> 
> - Host – Message store data host
> - Port – Message store data port
> - Masking – A multi-state variable (None, abbreviated, full) for
> masking email addresses at the results (we don’t want the emails to be
> spammed)
> 
> Interface to the Mailman core
> 
> - Metrics class – When a new post is sent, the Metrics class will
> receive it through the IArchiver interface. The Posts field of the
> Mailing List model (as well as the the related rows on the Month and
> Year models) will increase by one. If the author’s email is not in the
> database, it will query the mailman core database with the email, grab
> the author’s id and a new Author row will be created. Otherwise if the
> author is already in the database, the Posts field and the two foreign
> fields (Month and Year) will increase by one
> 
> - Generate class – When the ‘Generate’ button on the Admin page is pressed:
> * The Django models will be initialized (the metrics will go back to
> zero). A progress bar will inform the administrator that the operation
> is being processed.
> * All the messages of the archive will be parsed by performing a
> direct Python call to the IArchiver. Another instance to the IArchiver
> will grab any mails sent while the parsing is going on.
> * The metrics will be generated from scratch.
> * The administrator will be informed with a success message when the
> process is over.
> 
> [1]: http://sophron.latthi.com/gsoc-mailman/
> 
> -- 
> George Chatzisofroniou
> sophron.latthi.com
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