Information mining from public mailing lists: A case study on IETF mailing lists

Heiko Niedermayer; Nikolai Schwellnus; Daniel Raumer; Edwin Cordeiro; Georg Carle

doi:10.1007/978-3-319-70284-1_23

Information mining from public mailing lists: A case study on IETF mailing lists

Heiko Niedermayer, Nikolai Schwellnus, Daniel Raumer, Edwin Cordeiro, Georg Carle

Informatics 8 - Chair of Network Architectures and Services

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

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.

Original language	English
Title of host publication	Internet Science - 4th International Conference, INSCI 2017, Proceedings
Editors	Donald McMillan, Georg Carle, Antonella Passani, Jonathan Cave, Ioannis Kompatsiaris, Anna Satsiou, Efstratios Kontopoulos, Sotiris Diplaris
Publisher	Springer Verlag
Pages	301-309
Number of pages	9
ISBN (Print)	9783319702834
DOIs	https://doi.org/10.1007/978-3-319-70284-1_23
State	Published - 2017
Event	4th International Conference on Internet Science, INSCI 2017 - Thessaloniki, Greece Duration: 22 Nov 2017 → 24 Nov 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10673 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Conference on Internet Science, INSCI 2017
Country/Territory	Greece
City	Thessaloniki
Period	22/11/17 → 24/11/17

Keywords

Clustering
Identity deduplication
Mailing lists
Standardization

Access to Document

10.1007/978-3-319-70284-1_23

Cite this

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 D. McMillan, G. Carle, A. Passani, J. Cave, I. Kompatsiaris, A. Satsiou, E. Kontopoulos, & S. Diplaris (Eds.), Internet Science - 4th International Conference, INSCI 2017, Proceedings (pp. 301-309). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10673 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-70284-1_23

Niedermayer, Heiko ; Schwellnus, Nikolai ; Raumer, Daniel et al. / Information mining from public mailing lists : A case study on IETF mailing lists. Internet Science - 4th International Conference, INSCI 2017, Proceedings. editor / Donald McMillan ; Georg Carle ; Antonella Passani ; Jonathan Cave ; Ioannis Kompatsiaris ; Anna Satsiou ; Efstratios Kontopoulos ; Sotiris Diplaris. Springer Verlag, 2017. pp. 301-309 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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author = "Heiko Niedermayer and Nikolai Schwellnus and Daniel Raumer and Edwin Cordeiro and Georg Carle",

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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 D McMillan, G Carle, A Passani, J Cave, I Kompatsiaris, A Satsiou, E Kontopoulos & S Diplaris (eds), Internet Science - 4th International Conference, INSCI 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10673 LNCS, Springer Verlag, pp. 301-309, 4th International Conference on Internet Science, INSCI 2017, Thessaloniki, Greece, 22/11/17. https://doi.org/10.1007/978-3-319-70284-1_23

Information mining from public mailing lists: A case study on IETF mailing lists. / Niedermayer, Heiko; Schwellnus, Nikolai; Raumer, Daniel et al.
Internet Science - 4th International Conference, INSCI 2017, Proceedings. ed. / Donald McMillan; Georg Carle; Antonella Passani; Jonathan Cave; Ioannis Kompatsiaris; Anna Satsiou; Efstratios Kontopoulos; Sotiris Diplaris. Springer Verlag, 2017. p. 301-309 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10673 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Information mining from public mailing lists

T2 - 4th International Conference on Internet Science, INSCI 2017

AU - Niedermayer, Heiko

AU - Schwellnus, Nikolai

AU - Raumer, Daniel

AU - Cordeiro, Edwin

AU - Carle, Georg

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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PB - Springer Verlag

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ER -

Niedermayer H, Schwellnus N, Raumer D, Cordeiro E, Carle G. Information mining from public mailing lists: A case study on IETF mailing lists. In McMillan D, Carle G, Passani A, Cave J, Kompatsiaris I, Satsiou A, Kontopoulos E, Diplaris S, editors, Internet Science - 4th International Conference, INSCI 2017, Proceedings. Springer Verlag. 2017. p. 301-309. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-70284-1_23

Information mining from public mailing lists: A case study on IETF mailing lists

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