Open Source Tools: MUSE

Today I offer my third post in a series based on NARA’s 2015 report “Open Source Tools for Records Management.”  I investigated MUSE (Memories USing Email), which was developed at Stanford University. It is available for use in a Windows, Mac, or Linux environment.  I conducted my tests using Windows.

This program is a visualization tool for analyzing emails.  It is still in active development, and it currently incorporates six tools:

  • tabulates topics
  • charts sentiments
  • tracks the ingress and egress of email correspondents and groups people who “go together” based on their receipt of messages
  • allows you to browse attachments on a Piclens 3D photo wall
  • offers the possibility of personalizing web pages by highlighting terms also found in your email (requires the use of a browser extension)
  • creates crossword puzzles based on your email archive

muse_acct-typeOnce you download the executable file from the above site, the program runs locally on your computer.  Muse can be deployed on a static archive of email messages (e.g., an mbox file) or it can fetch email from online accounts for which you have the email address, password, and server settings.  It defaults to analyzing Sent mail, based on the principle that those messages more accurately reflect the topics and people with which the account owner is most engaged, but you can also include additional folders.  You can then browse all messages in the embedded viewer — without having to open each message individually — or you can use any of the tools listed above.

muse_sentimentsThe sentiment analyzer using natural language processing and a built-in lexicon, but it can be customized by the user to identify desired terms (see Edit Lexicon highlighted above to access the screen below).

muse_lexiconAccording to their tip sheet for journalists, MUSE “was originally meant for people to browse their own long-term email archives.  We have now started adapting it for journalists, archivists and researchers.”  Due to the ease of use of this lightweight tool, this could be an easy way for repositories to provide an email analysis tool to researchers.  This same tip sheet defines the “sweet spot” for the software as archives with about 50,000 messages.

If you’re interested in learning more about MUSE, a Ph.D. dissertation and a number of papers are available here.  There’s also a video that argues for the value of analyzing personal digital archives.  This project dovetails with the work being done at Stanford on ePADD — check out our Hangout for more information on that project.

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