A survey on email visualisation research to address the conflict between privacy and access

Author:

Bartliff ZoeORCID,Kim Yunhyong,Hopfgartner Frank

Abstract

AbstractEmails, much like communicative genres such as letters that predate them, are a rich source of data for researchers, but they are replete with privacy considerations. This paper explores the resulting friction between privacy concerns and email data access. Studies of email can often be centred on understanding patterns of behaviour and/or relationships between people or groups, and, as such, embody risks of disclosing private information. This is further amplified in humanities research which is concerned with the individual, their work and the circumstances that influence them. Furthermore, previous studies have expounded upon the benefits of visualisations for researching email data, a method which has been reported both as a path to addressing known concerns, as well as, introducing new concerns in privacy. The spectrum of methodologies leave archivists and curators of email data in a quandary, unable to balance accessibility with privacy. The research presented in this paper contributes a systematic approach to examining the relationship between email visualisation research and privacy. It presents a categorisation of email visualisation attributes, and a graded scale of privacy, to be used in conjunction as a framework for interrogating existing research and their associated email collections. The paper aims to instigate the first steps in concretely situating the extent to which research can take advantage of or is challenged by privacy conscious data management.

Funder

Arts and Humanities Research Council

University of Glasgow

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,History

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards privacy-aware exploration of archived personal emails;International Journal on Digital Libraries;2024-02-21

2. Contextual Forensic Analysis of Emails Using Machine Learning Algorithms;2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT);2024-02-09

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