Publication: Temporal dynamics and success patterns of online petitions: a time-series clustering approach
Temporal dynamics and success patterns of online petitions: a time-series clustering approach
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Kovacs, M., Buryakov, D., Gohourou, D., & Serdült, U. (2025). Temporal dynamics and success patterns of online petitions: a time-series clustering approach. 103–109. https://doi.org/10.1145/3728985.3728996
Abstract
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Online petition systems worldwide enable individuals to express about public life issues. Usually, these systems require a certain threshold of digital endorsements to be met within a given timeline before a petition can reach the authorities. In the Taiwan’s JOIN platform the requirement is 5000 signatures within 60 days. However, the dynamics of endorsements for online petitions can vary greatly over time. An analysis of all admitted online petitions since 2015, applying Dynamic Time Warping and k-means clustering, produced three cl
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- Kovacs, Mate
- Buryakov, Daniil
- Gohourou, Didier
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Kovacs, M., Buryakov, D., Gohourou, D., & Serdült, U. (2025). Temporal dynamics and success patterns of online petitions: a time-series clustering approach. 103–109. https://doi.org/10.1145/3728985.3728996
