The exponential growth of mobile apps within the Android ecosystem has underscored the critical need for robust user privacy and data protection measures. Central to these concerns are the privacy policies that serve ...
详细信息
ISBN:
(纸本)9783031777301;9783031777318
The exponential growth of mobile apps within the Android ecosystem has underscored the critical need for robust user privacy and data protection measures. Central to these concerns are the privacy policies that serve as the primary channel of communication between organizations and users, detailing data collection, utilization, and sharing practices. However, the efficacy of these policies is often undermined by their inaccessibility and the legalese that obfuscates their intent, presenting a barrier to informed user consent. This study addresses these challenges by harnessing the capabilities of Generative AI (GenAI) to perform a detailed analysis of data practices in Android apps. Our methodology extends beyond the traditional scope of AI-assisted analysis by not only identifying third-party entities but also by elucidating their data handling purposes. We introduce a classification system that distinguishes between 'Regular' and 'Irregular' app behaviors, offering a benchmark for app evaluation and compliance assessment. Our comparative analysis across various apps reveals patterns and anomalies in data management, providing actionable insights for developers, regulators, and users.
In order to improve our understanding of scientific datausers’ data usage behaviors, which has been rarely studiedin the fourth science paradigm-data-intensive science, thisstudy conducted a content analysis of publi...
详细信息
ISBN:
(纸本)0877155429
In order to improve our understanding of scientific data
users’ data usage behaviors, which has been rarely studied
in the fourth science paradigm-data-intensive science, this
study conducted a content analysis of publications
associated with a frequently cited data-intensive science
project, called Sloan Digital Sky Survey (SDSS). We
analyzed 200 SDSS-related publications and identified the
data used in each publication. Under the scope of SDSS
project, we found that (1) nearly half studies used one data
source only. A few studies were able to use three or more
data sources; (2) studies that analyzed a small number of
objects are the norm; (3) users are not only consumers of
scientific data. They are also data producers; (4) studies that
can utilize multiple large scale data sources are rare.
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