Information Mining from Public Mailing Lists: A Case Study on IETF Mailing Lists

摘要

Public mailing lists, such as the mailing lists used by the IETF for Internet Standardization, can be used as big real world data set for analysis of social interactions. However, volatile participation and the usage of mail addresses as changeable pseudonyms constitute a challenge for data mining in these data. We conducted a case study of mailing list analysis wherein we address the consistent identification of a person with all of her contributions to be used as panel data. Based on the postings of individuals on different mailing lists, correlations between standardization areas in the IETF groups can be computed. Isolated and meshed standardization areas can be identified.