Mining email social networks

Abstract

Communication & Co-ordination activities are central to large software projects, but are difficult to observe and study in traditional (closed-source, commercial) settings because of the prevalence of informal, direct communication modes. OSS projects, on the other hand, use the internet as the communication medium, and typically conduct discussions in an open, public manner. As a result, the email archives of OSS projects provide a useful trace of the communication and co-ordination activities of the participants. However, there are various challenges that must be addressed before this data can be effectively mined. Once this is done, we can construct social networks of email correspondents, and begin to address some interesting questions. These include questions relating to participation in the email; the social status of different types of OSS participants; the relationship of email activity and commit activity (in the CVS repositories) and the relationship of social status with commit activity. In this paper, we begin with a discussion of our infrastructure and then discuss our approach to mining the email archives; and finally we present some preliminary results from our data analysis.

Social Activities Rival Patch Submission for Prediction of Developer Initiation in OSS Projects

“…While the data on mailing list communications within projects are readily available, as are code commits and changes, patches and bug identification data is more difficult to gather [11] since it requires parsing message texts and mining multiple sources of predicting developers both when patch information is available and also when it is not. Early in their tenure as OSS project participants, people's patterns of technical and social activities are rapidly changing.…”

“…It is a general policy for OSS projects to channel as much communication as possible through project mailing lists so that all participants can benefit from the exchange of ideas and information [11]. Any message sent to these lists will be broadcast to all subscribed participants.…”

“…Even given this difficulty, however, we can still infer a communication network. When person A sends message M , in response to message N , that was sent by person B, then there is a high chance that A primarily intended to communicate to B in response to their initial message that was broadcast to no particular recipient [11]. Such links are in fact two-way social links, in that the communication occurs both ways.…”

“…Since these aliases represent a single person they must be merged if we are to accurately capture an individual's social activity. Unmasking aliases is a well-known problem in the literature [11], [19], [20]. Bird et al used a string similarity based approach to address this problem [11].…”

“…Unmasking aliases is a well-known problem in the literature [11], [19], [20]. Bird et al used a string similarity based approach to address this problem [11]. We improved and automated their procedure reducing the need for human interaction.…”