Abstract
Software End User License Agreements (EULAs) are notoriously dense legal documents that users often skim over without fully understanding their implications, including privacy-related clauses. This research proposes a novel approach to improve the readability and privacy awareness of EULAs by implementing a nudge tool to improve user attention and comprehension of EULA contents. Through natural language processing technique, privacy-sensitive keywords within EULAs are identified and visually emphasized for users. By drawing attention to EULA clauses related to data collection, sharing, and security, users can make more informed decisions about their privacy when agreeing to software terms. Detailed user experiments involving 173 participants are performed to evaluate the effectiveness of the proposed approach demonstrating significant improvements in comprehension and awareness of privacy implications compared to traditional EULAs. The developed nudge tool is released and made freely available for the interesting readers (https://github.com/Data-and-Design-Lab/EULA-plugin/).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Acquisti, A., et al.: Nudges for privacy and security: understanding and assisting users’ choices online. ACM Comput. Surv. (CSUR) 50(3), 1–41 (2017)
Alabduljabbar, A., Abusnaina, A., Meteriz-Yildiran, Ü., Mohaisen, D.: TLDR: deep learning-based automated privacy policy annotation with key policy highlights. In: Proceedings of the 20th Workshop on Workshop on Privacy in the Electronic Society, pp. 103–118 (2021)
Anderson, J.: Nudge: improving decisions about health, wealth, and happiness, Richard H. Thaler and Cass R. Sunstein. Yale University Press, 2008. x+ 293 pages. [paperback edition, penguin, 2009, 320 pages.]. Econ. Philos. 26(3), 369–376 (2010)
Binns, R., Matthews, D.: Community structure for efficient information flow in ‘tos; dr’, a social machine for parsing legalese. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 881–884 (2014)
Brunotte, W., Chazette, L., Kohler, L., Klunder, J., Schneider, K.: What about my privacy? Helping users understand online privacy policies. In: Proceedings of the International Conference on Software and System Processes and International Conference on Global Software Engineering, pp. 56–65 (2022)
Bui, D., Shin, K.G., Choi, J.-M., Shin, J.: Automated extraction and presentation of data practices in privacy policies. In: Proceedings on Privacy Enhancing Technologies (2021)
Butters, R.R.: Trademark linguistics: trademarks: language that one owns. In: The Routledge Handbook of Forensic Linguistics, pp. 364–381. Routledge (2020)
Campos, R., Mangaravite, V., Pasquali, A., Jorge, A., Nunes, C., Jatowt, A.: Yake! keyword extraction from single documents using multiple local features. Inf. Sci. 509, 257–289 (2020)
Cao, N., Wang, C., Li, M., Ren, K., Lou, W.: Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 25(1), 222–233 (2013)
Caraban, A., Karapanos, E., Gonçalves, D., Campos, P.: 23 ways to nudge: a review of technology-mediated nudging in human-computer interaction. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–15 (2019)
Castleman, B.L., Page, L.C.: Summer nudging: can personalized text messages and peer mentor outreach increase college going among low-income high school graduates? J. Econ. Behav. Organ. 115, 144–160 (2015)
Cherry, M.A.: A eulogy for the Eula. Duq. L. Rev. 52, 335 (2014)
Cranor, L.F.: P3P: making privacy policies more useful. IEEE Secur. Privacy 1(6), 50–55 (2003)
Cranor, L.F., Reagle, J., Ackerman, M.S.: Beyond concern: understanding net users’ attitudes about online privacy (2000)
Cutler, A., Rivest, J., Cavanagh, P.: The role of memory color in visual attention. Attention Perception Psychophysics 86(1), 28–35 (2024)
Desautels, E.: Software license agreements: ignore at your own risk
Dowthwaite, L., et al.: “It’s your private information. it’s your life”. Young people’s views of personal data use by online technologies. In: Proceedings of the Interaction Design and Children Conference, pp. 121–134 (2020)
Ericson, J.D., Albert, W.S., Bernard, B.P., Brown, E.: End-user license agreements (eulas) investigating the impact of human-centered design on perceived usability, attitudes, and anticipated behavior. Inf. Des. J. 26(3), 193–215 (2021)
Grootendorst, M.: Keyword extraction with BERT. Towards Data Science (2021)
Halpern, D., Sanders, M.: Nudging by government: progress, impact, & lessons learned. Behav. Sci. Policy 2(2), 53–65 (2016)
Hardeniya, N., Perkins, J., Chopra, D., Joshi, N., Mathur, I.: Natural Language Processing: Python and NLTK. Packt Publishing Ltd. (2016)
Hsieh, P.-H., Hsu, P.-I.: Displaying software installation agreements to motivate users’ reading. Int. J. Hum.-Comput. Interact. 1–18 (2022)
Jacowitz, K.E., Kahneman, D.: Measures of anchoring in estimation tasks. Pers. Soc. Psychol. Bull. 21(11), 1161–1166 (1995)
Khan, B., Syed, T., Khan, Z., Rafi, M.: Textual analysis of end user license agreement for red-flagging potentially malicious software. In: 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), pp. 1–5. IEEE (2020)
Kortum, P.T., Bangor, A.: Usability ratings for everyday products measured with the system usability scale. Int. J. Hum.-Comput. Interact. 29(2), 67–76 (2013)
Kretschmer, M., Pennekamp, J., Wehrle, K.: Cookie banners and privacy policies: measuring the impact of the GDPR on the web. ACM Trans. Web (TWEB) 15(4), 1–42 (2021)
Liu, F., Wilson, S., Story, P., Zimmeck, S., Sadeh, N.: Towards automatic classification of privacy policy text. School of Computer Science Carnegie Mellon University (2018)
Manandhar, S., Singh, K., Nadkarni, A.: Towards automated regulation analysis for effective privacy compliance. In: ISOC Network and Distributed System Security Symposium (2024)
McDonald, A.M., Reeder, R.W., Kelley, P.G., Cranor, L.F.: A comparative study of online privacy policies and formats. In: Goldberg, I., Atallah, M.J. (eds.) PETS 2009. LNCS, vol. 5672, pp. 37–55. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03168-7_3
Nowrozy, R., Ahmed, K., Kayes, A.S.M., Wang, H., McIntosh, T.R.: Privacy preservation of electronic health records in the modern era: a systematic survey. ACM Comput. Surv. (2024)
Obar, J.A., Oeldorf-Hirsch, A.: The biggest lie on the internet: ignoring the privacy policies and terms of service policies of social networking services. Inf. Commun. Soc. 23(1), 128–147 (2020)
Ortloff, A.-M., Zimmerman, S., Elsweiler, D., Henze, N.: The effect of nudges and boosts on browsing privacy in a naturalistic environment. In: Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, pp. 63–73 (2021)
Pollach, I.: What’s wrong with online privacy policies? Commun. ACM 50(9), 103–108 (2007)
Regulwar, G.B., Majji, R., Kottu, S.K., Kachi, A., Sureddy, R.R.: Content analysis and visualization of privacy policy using privacy management. In: AIP Conference Proceedings, vol. 2942. AIP Publishing (2024)
Reinhardt, D., Borchard, J., Hurtienne, J.: Visual interactive privacy policy: the better choice? In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1–12 (2021)
Richardson, L.: Beautiful soup documentation (2007)
Stiglitz, J., Barkley Rosser, J., et al.: A Nobel prize for asymmetric information: the economic contributions of George Akerlof, Michael Spence and Joseph Stiglitz. In: Leading Contemporary Economists, pp. 162–181. Routledge (2008)
Rossi, A., Palmirani, M.: A visualization approach for adaptive consent in the European data protection framework. In: 2017 Conference for E-Democracy and Open Government (CeDEM), pp. 159–170. IEEE (2017)
Schellekens, M.: Is an icon worth a thousand words? Grounded legal strategies for standardised icons under the GDPR (2023)
Schufrin, M., Reynolds, S.L., Kuijper, A., Kohlhammer, J.: A visualization interface to improve the transparency of collected personal data on the Internet. IEEE Trans. Vis. Comput. Graph. 27(2), 1840–1849 (2020)
Simon, H.A.: Models of Bounded Rationality: Empirically Grounded Economic Reason, vol. 3. MIT Press, Cambridge (1997)
Solove, D.J.: The myth of the privacy paradox. Geo. Wash. L. Rev. 89(1) (2021)
Tversky, A., Kahneman, D.: Judgment under uncertainty: heuristics and biases: biases in judgments reveal some heuristics of thinking under uncertainty. Science 185(4157), 1124–1131 (1974)
Waddell, T.F., Auriemma, J.R., Sundar, S.S.: Make it simple, or force users to read? paraphrased design improves comprehension of end user license agreements. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 5252–5256 (2016)
Zhang, S., Sadeh, N.: Do privacy labels answer users’ privacy questions? In: Workshop on Usable Security and Privacy (2023)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Ethics declarations
Ethics and Safety
For the user studies described in this paper, we received an Institutional Review Board (IRB) certificate for human subjects research, approved study questionnaire, and ensured no personally identifiable data was collected from the participants.
Rights and permissions
Copyright information
© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Zahid, S.B., Bristy, A.G., Oli, M.M.H., Fahim, M., Rumee, S.T.A., Zaber, M.I. (2025). Making EULA Great Again: A Novel Nudge Mechanism to Improve Readability, User Attention and Awareness. In: Patil, V.T., Krishnan, R., Shyamasundar, R.K. (eds) Information Systems Security. ICISS 2024. Lecture Notes in Computer Science, vol 15416. Springer, Cham. https://doi.org/10.1007/978-3-031-80020-7_20
Download citation
DOI: https://doi.org/10.1007/978-3-031-80020-7_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-80019-1
Online ISBN: 978-3-031-80020-7
eBook Packages: Computer ScienceComputer Science (R0)