Advancing Privacy Research: A Novel Realistic Persona-Based Dataset -- 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)
Academic Article
Overview
Identity
View All
Overview
Abstract
We introduce a unique approach to privacy research by creating a virtual persona that mimics human web-searching behaviors. The persona's activities, categorized into 'morning', 'afternoon', and 'evening', were automated using the Selenium WebDriver, enabling the persona to conduct searches as a real user would. The resulting dataset comprises 1,537 records, each representing a unique search query. Each record contains the first two pages of a query result, including the query keywords and a list of the first 2 pages of the query result. The study offers a fresh perspective on the study of privacy and personalization in online environments. The potential for reusing this dataset is significant, as it can be applied to studies on privacy, data collection, and search engine personalization, and it can be used to develop and test algorithms and models that aim to protect user privacy. Furthermore, this work not only produces a dataset but also establishes the framework for generating additional similar datasets that can serve the purpose of conducting more comprehensive research on search engines.
