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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bettenburg, N., Shihab, E., Hassan, A.E.: An empirical study on the risks of using off-the-shelf techniques for processing mailing list data. In: 2009 IEEE International Conference on Software Maintenance, pp. 539–542. Edmonton, Alberta, Canada, September 2009
Bird, C., Gourley, A., Devanbu, P.T., Gertz, M., Swaminathan, A.: Mining email social networks. In: Proceedings of the 2006 International Workshop on Mining Software Repositories, MSR 2006, pp. 137–143. Shanghai, China, May 2006
Borgatti, S.P., Mehra, A., Brass, D.J., Labianca, G.: Network analysis in the social sciences. Science 323(5916), 892–895 (2009)
Chen, H., Shen, H., Xiong, J., Tan, S., Cheng, X.: Social network structure behind the mailing lists: ICT-IIIS at TREC 2006 expert finding track. In: Proceedings of the Fifteenth Text REtrival Conference, TREC 2006, Gaithersburg, Maryland, USA, November 2006
Granovetter, M.S.: The strength of weak ties. Am. J. Sociol. 78(6), 1360–1380 (1973)
Jensen, C., King, S., Kuechler, V.: Joining free/open source software communities: an analysis of newbies’ first interactions on project mailing lists. In: 2011 44th Hawaii International Conference on System Sciences, pp. 1–10, January 2011
Junior, M.C., Mendonca, M., Farias, M., Henrique, P.: OSS developers context-specific preferred representational systems: a initial neurolinguistic text analysis of the apache mailing list. In: 7th IEEE Working Conference on Mining Software Repositories, MSR 2010, pp. 126–129, May 2010
Marín, S.L.T., Martínez-Torres, M.R., Barrero, F.: Modelling mailing list behaviour in open source projects: the case of ARM embedded linux. J. UCS 15(3), 648–664 (2009)
Meijuan, Y., Qingxian, W., Shuming, C., Xiaonan, L., Xiangyang, L.: Ranking the authority of name aliases for email users. In: 2011 Third International Conference on Multimedia Information Networking and Security, pp. 425–430, November 2011
Niedermayer, H., Raumer, D., Schwellnus, N., Cordeiro, E., Carle, G.: An analysis of IETF activities using mailing lists and social media. In: Bagnoli, F., Satsiou, A., Stavrakakis, I., Nesi, P., Pacini, G., Welp, Y., Tiropanis, T., DiFranzo, D. (eds.) INSCI 2016. LNCS, vol. 9934, pp. 218–230. Springer, Cham (2016). doi:10.1007/978-3-319-45982-0_19
Yoo, S., Yang, Y., Lin, F., Moon, I.C.: Mining social networks for personalized email prioritization. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2009, New York, pp. 967–976. ACM, June 2009
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Niedermayer, H., Schwellnus, N., Raumer, D., Cordeiro, E., Carle, G. (2017). Information Mining from Public Mailing Lists: A Case Study on IETF Mailing Lists. In: Kompatsiaris, I., et al. Internet Science. INSCI 2017. Lecture Notes in Computer Science(), vol 10673. Springer, Cham. https://doi.org/10.1007/978-3-319-70284-1_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-70284-1_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70283-4
Online ISBN: 978-3-319-70284-1
eBook Packages: Computer ScienceComputer Science (R0)