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

Autor:	Heiko Niedermayer, Nikolai Schwellnus, Georg Carle, Edwin Cordeiro, Daniel Raumer
Rok vydání:	2017
Předmět:	World Wide Web Set (abstract data type) Identification (information) Standardization Computer science business.industry Information mining The Internet Mailing list Cluster analysis business GeneralLiterature_REFERENCE(e.g. dictionaries encyclopedias glossaries) Panel data
Zdroj:	Internet Science ISBN: 9783319702834 INSCI
DOI:	10.1007/978-3-319-70284-1_23
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::32e1c72287c017e30fd4c98d6113b60b https://doi.org/10.1007/978-3-319-70284-1_23 Zobrazit plný text záznamu