List of Tools

MailingListStats

• URL: http://tools.libresoft.es/mailing_list_stats
• Author: Israel Herraiz <herraiz at gsyc.escet.urjc.es>.
• Description: MailingListStats is a tool for mapping mbox files of any mailing list to a database.
• Technologies: Python, MySQL.
• Execution mode:
  • Please read the little 'How To' in the README file.
• Input data: URLs of each mailing list or a directory with the mboxes of each mailing list separated by directories.
• Output data: Database with information about headers of each parsed mbox and its mailing list.
• Technology limitation:
  • Each mailing list database cannot be updated without reparsed all mailing list again.
  • Duplicated information is stored in the database when MLS is running using a mbox of a mailing list studied previously.
  • Not fault tolerat. MLS cannot resume its work when the system down unannounced. Is needed to run MLS from the beginning for all mailing lists.
• Maturity: alpha.
• Dependencies: python, mysql.
• Documentation:
  • http://tools.libresoft.es/mailing_list_stats
  • libresoft-tools-devel
• License: GNU General Public License (GPL).
• Metrics:
  • Name of the poster.
  • Number of non-active developers.
  • Name of the poster.
  • E-mail address of the poster.
  • Date when the messsage was sent by the poster, and received in the mailing list server.
  • Subject of the message.
  • Mailing list address where the message was sent to.
  • Name and e-mail addresses of other recipients different of the list (for example, other people include in the CC field of the message).
  • Unique identification tag for the message in the mailing list.
  • Identification tag of the original message if the message is a reply to another.
  • Content of the message, including usually attachments.
  • Name of the program used to write the message.
  • Activity (number of messages).
  • Participation (number of people participating).
  • Number of messages over time.
  • Number of people writing in the list over time.
  • SNA methods to study the flow of information within the community. Evolution over time.
  • Mean length of the threads over time. Standard deviation.
  • Statistics of usage of the different programs in the mailing list.
  • List of keywords of the topics discussed in the lists.
  • The list of keywords could be obtained in a monthly basis.
  • With a list of keyword for each month, we can find out which topics were the most discussed and if the topics have evolved.
  • Can be crossed correlated topics with people involved in the discussion of those topics.