Awareness of privacy and data collection: exploring privacy policy effectiveness in Google Maps

Introduction Concerns over privacy and data collection have become increasingly important since software is everywhere. Apps such as Google Maps collect data on users' whereabouts, interests, habits, and more. Method Data collection practices are typically delivered through a privacy policy. To evaluate the effectiveness of privacy policies, we focus on Google Maps as a concrete and widely used app example. Our study explores user perspectives on privacy concerning the Google Maps app, and combines them with prior research to assess user awareness of data collection and privacy. To achieve our objective, we use a survey containing 19 questions (aligned with the themes explored in the state of the art, i.e., privacy policy awareness, users' habits regarding privacy, the effectiveness of privacy policies). The sampling strategy is a convenience one to receive the greatest number of responses. The received answers are analyzed by focusing on the readability and understandability of privacy policies. Results The output indicates that privacy policies are complex, require a significant amount of time to be read, hard to understand by most of the users, and, hence, ignored by most of the users. Discussion The various reasons why privacy policies are ineffective and what causes users to avoid reading them are summarized and discussed. Potential solutions to the inefficacy of privacy policies are outlined and areas/hints for further research are revealed.

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Publication Details

Journal
Frontiers in Computer Science
Published
2025-09-24
DOI
https://doi.org/10.3389/fcomp.2025.1568179
Citations
1
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
4.20
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article

Awareness of privacy and data collection: exploring privacy policy effectiveness in Google Maps

Claudia Raibulet, Kevin I‐Kai Wang
1 citations
Frontiers in Computer Science
Privacy, Security, and Data Protection
4.20
article

Awareness of privacy and data collection: exploring privacy policy effectiveness in Google Maps

Claudia Raibulet, Kevin I‐Kai Wang
article en
1 citations

Abstract

Introduction Concerns over privacy and data collection have become increasingly important since software is everywhere. Apps such as Google Maps collect data on users' whereabouts, interests, habits, and more. Method Data collection practices are typically delivered through a privacy policy. To evaluate the effectiveness of privacy policies, we focus on Google Maps as a concrete and widely used app example. Our study explores user perspectives on privacy concerning the Google Maps app, and combines them with prior research to assess user awareness of data collection and privacy. To achieve our objective, we use a survey containing 19 questions (aligned with the themes explored in the state of the art, i.e., privacy policy awareness, users' habits regarding privacy, the effectiveness of privacy policies). The sampling strategy is a convenience one to receive the greatest number of responses. The received answers are analyzed by focusing on the readability and understandability of privacy policies. Results The output indicates that privacy policies are complex, require a significant amount of time to be read, hard to understand by most of the users, and, hence, ignored by most of the users. Discussion The various reasons why privacy policies are ineffective and what causes users to avoid reading them are summarized and discussed. Potential solutions to the inefficacy of privacy policies are outlined and areas/hints for further research are revealed.

Frontiers in Computer ScienceVol. 7
University of Milan (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Milano Bicocca (IT), University of Milano-Bicocca (IT), Vrije Universiteit Amsterdam (NL)
Openalex Percentile: Top 6%
Privacy, Security, and Data Protection
4.20
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Awareness of privacy and data collection: exploring privacy policy effectiveness in Google Maps — Claudia Raibulet, Kevin I‐Kai Wang · Frontiers in Computer Science (2025) | TGRS Research Map | TGRS