@inproceedings{3f09259d7f734989abe9408470cefd79,
title = "Information mining from public mailing lists: A case study on IETF mailing lists",
abstract = "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.",
keywords = "Clustering, Identity deduplication, Mailing lists, Standardization",
author = "Heiko Niedermayer and Nikolai Schwellnus and Daniel Raumer and Edwin Cordeiro and Georg Carle",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 4th International Conference on Internet Science, INSCI 2017 ; Conference date: 22-11-2017 Through 24-11-2017",
year = "2017",
doi = "10.1007/978-3-319-70284-1\_23",
language = "English",
isbn = "9783319702834",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "301--309",
editor = "Donald McMillan and Georg Carle and Antonella Passani and Jonathan Cave and Ioannis Kompatsiaris and Anna Satsiou and Efstratios Kontopoulos and Sotiris Diplaris",
booktitle = "Internet Science - 4th International Conference, INSCI 2017, Proceedings",
}