Leaky Democracy : Third Parties in Voting Advice Applications
: Heino, Timi; Rauti, Sampsa; Laato, Samuli; Carlsson, Robin; Leppänen, Ville
: Senjyu, T., So-In, C., Joshi, A.
: International Conference on Smart Trends in Computing and Communications
Publisher: Springer Science and Business Media Deutschland GmbH
: 2024
: Lecture notes in networks and systems
: Smart Trends in Computing and Communications : Proceedings of SmartCom 2024, Volume 5
: Lecture Notes in Networks and Systems
: 949
: 351
: 360
: 978-981-97-1312-7
: 978-981-97-1313-4
: 2367-3370
: 2367-3389
DOI: https://doi.org/10.1007/978-981-97-1313-4_30
: https://link.springer.com/chapter/10.1007/978-981-97-1313-4_30
: https://research.utu.fi/converis/portal/detail/Publication/457080223
An important part of democracy is the premise of ballot secrecy, where each individual can vote privately without interference, and without anyone getting to say what they vote for. Legislation such as GDPR also indicates that a person’s political opinion is sensitive personal data. Yet, in the modern technological era, there are countless ways through which people’s political views can be probed, stored and in the worst cases, manipulated. One avenue through which this can happen are voting advice applications, online tools designed for helping people in selecting optimal candidates during elections. In this work, we performed a network traffic analysis of Finnish voting advice applications during the parliamentary election of Spring 2023, to see whether any sensitive information regarding, for example, the persons’ political opinions, is leaked to third parties through the available voting advice applications. The results revealed that in 7 out of 11 analyzed applications, this was the case. Our work offers empirical evidence showing that while there may still be secrecy in the voting booth, the steps leading to the booth are paved with data leaks. We conclude the study by discussing the assurance of democratic processes and systems in our modern socio-digital society.
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This research has been funded by Academy of Finland project 327397, IDA—Intimacy in Data-Driven Culture.
