As reported by Kevin Crowston and co-authors in a recent paper, free open source software is a very important social phenomenon that involves nearly one million programmers, a myriad of software development firms, millions of users, and its financial impact is huge since for instance the cost of recreating available free software is estimated in tens of billions of euros. Free open source software projects generally have one mailing list for developers and another one for users. This large number of mailing lists changes constantly and shows a great variety with respect to membership and topics covered. This makes them very difficult to monitor. One way of overcoming this Big Data Challenge is to identify some easily computable global indicators that can be used for instance to detect important events. We illustrate this approach here by making a social network analysis and comparison of developers' and users' mailing lists of four free open source software projects: CentOS, GnuPG, Mailman and Samba. We show that these mailing lists have some common characteristics : the number of messages, the time durations and the interlink times can be fitted using power and lognormal laws with suitable scales and parameters ; for the interlink time, the analysis is done using the temporal delta density inspired by the delta density introduced by Viard and Latapy. This similarity between the characteristics of mailing lists also applies to the structure of dominant groups. For the time evolution of the number of messages, GnuPG exhibits a particular behavior. The interpretation of the different parameters gives very interesting insights into the membership and the type of topics covered by the mailing lists. The analysis carried out here and similar studies cited in this paper can therefore be considered as a first step towards the designing of building blocks for monitoring mailing lists.