Citizen Privacy Framework (eBook)

Case of a Fuzzy-based Recommender System for Political Participation

Aigul Kaskina (Autor)

eBook Download: PDF

2022 | 1st ed. 2022
XVII, 110 Seiten
Springer International Publishing (Verlag)
978-3-031-06021-2 (ISBN)

Infos

This book presents the concept of a fuzzy-based recommender system for user account privacy settings that can be used for citizen participation on online political platforms. The elaborated components are exemplarily based on the needs of a political platform implemented during the presidential election in Ecuador. The book readdresses the issue of privacy paradox demonstrating that, indeed, users' actual decisions of being private in most cases diverge with their initial privacy intentions. The two concepts presented in the book - the citizen privacy profile framework and the prototype fuzzy-based privacy settings recommender system - can be adapted by different organizations such as government institutions, NGOs, or private online service providers to meet their specific needs.  
The book will be of interest to researchers and practitioners in the areas of usage modeling, privacy, system design, and for service providers in eDemocracy.

Aigul Kaskina acquired the degree of Doctor of Philosophy in Computer Science from University of Fribourg, Switzerland.  Currently she is working as a Data & AI scientist at Accenture based in Zurich, Switzerland. Her main focus is on data analytics, big data, artificial intelligence and machine learning.

Produkt-Details

• Erscheint lt. Verlag: 15.9.2022
• Reihe/Serie: Fuzzy Management Methods
• Reihe/Serie: Fuzzy Management Methods
• Zusatzinfo: XVII, 110 p. 33 illus., 27 illus. in color.
• Sprache: englisch
• Themenwelt: Informatik ► Netzwerke ► Sicherheit / Firewall
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management
• Schlagworte: Disclosure behavior • Fuzzy Clustering • machine learning • pattern recognition • Political participation • Privacy behavior • Privacy decision-making • Privacy profiles • Recommender Systems
• ISBN-10: 3-031-06021-0 / 3031060210
• ISBN-13: 978-3-031-06021-2 / 9783031060212