Dr CHRISTOPHER CARTER CHRISTOPHER.CARTER@NOTTINGHAM.AC.UK
ASSISTANT PROFESSOR IN ENTREPRENEURSHIP AND INNOVATION
Dr CHRISTOPHER CARTER CHRISTOPHER.CARTER@NOTTINGHAM.AC.UK
ASSISTANT PROFESSOR IN ENTREPRENEURSHIP AND INNOVATION
Ansgar Koene
Professor ELVIRA PEREZ VALLEJOS elvira.perez@nottingham.ac.uk
PROFESSOR OF DIGITAL TECHNOLOGY FOR MENTAL HEALTH
Ramona Statache
Professor SVENJA ADOLPHS SVENJA.ADOLPHS@NOTTINGHAM.AC.UK
PROFESSOR OF ENGLISH LANGUAGE AND LINGUISTICS
Claire O�Malley
Professor TOM RODDEN TOM.RODDEN@NOTTINGHAM.AC.UK
Pro-Vice-Chancellor of Research & Knowledge Exchange
Derek McAuley
Online search engines, social media, news sites and retailers are all investing heavily in the development of ever more refined information filtering to optimally tune their services to the specific demands of their individual users and customers. In this position paper we examine the privacy consequences of user profile models that are used to achieve this information personalization, the lack of transparency concerning the filtering choices and the ways in which personalized services impact the user experience. Based on these considerations we argue that the Internet research community has a responsibility to increase its efforts to investigate the means and consequences of personalized information filtering.
Carter, C. J., Koene, A., Perez, E., Statache, R., Adolphs, S., O’Malley, C., Rodden, T., & McAuley, D. (2015). Ethics of Personalized Information Filtering. In Internet Science (123-132). Springer Verlag. https://doi.org/10.1007/978-3-319-18609-2_10
Acceptance Date | May 9, 2015 |
---|---|
Publication Date | 2015 |
Deposit Date | Feb 26, 2018 |
Publicly Available Date | Feb 26, 2018 |
Journal | Internet Science; Lecture Notes in Computer Science |
Electronic ISSN | 0302-9743 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 9089 |
Pages | 123-132 |
Book Title | Internet Science |
DOI | https://doi.org/10.1007/978-3-319-18609-2_10 |
Keywords | Privacy, Transparency, Behavior manipulation, RRI, Filter bubble |
Public URL | https://nottingham-repository.worktribe.com/output/763646 |
Publisher URL | https://link.springer.com/chapter/10.1007%2F978-3-319-18609-2_10 |
Additional Information | The final publication is available at Springer via https://link.springer.com/chapter/10.1007%2F978-3-319-18609-2_10 |
Contract Date | Feb 26, 2018 |
ICISSGI15_EthicsOfPersonalizedInformationFilters_AKoeneEtAl_final_draft.pdf
(291 Kb)
PDF
Discomfort—the dark side of fun
(2018)
Book Chapter
Learning from the Veg Box: Designing Unpredictability in Agency Delegation
(2018)
Presentation / Conference Contribution
A Method for Evaluating Options for Motif Detection in Electricity Meter Data
(2018)
Journal Article
Bread stories: understanding the drivers of bread consumption for digital food customisation
(2017)
Presentation / Conference Contribution
Data Work: How Energy Advisors and Clients Make IoT Data Accountable
(2017)
Journal Article
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search