Abstract
Understanding and quantifying the sentiments of the constituency leads to more strategic and effective implementation of policies for both national and subnational governments. This study explores the use of feedback data mining and analytics to inform the proposed “Low-speed streets” policy of Pasig City. A survey with 45 topic-related statements and 8 metadata statements was voted on by a total of 423 voters over 18 days. Quantitative data were analyzed using timeline analysis, association analysis, and principal components analysis, while qualitative data were analyzed using natural language processing. Two opinion groups were identified: group A, which supports the low-speed streets, and group B, with hesitations on the implementation of low-speed streets. Results revealed that both groups agreed on the benefits of walking and cycling and the need for the city government to improve biking spaces and signages. They, however, disagree on whether cars should be prioritized on the roads over pedestrians and cyclists. Association analysis revealed that public belief in low-speed streets causing traffic is associated with beliefs that rigorous enforcement of speed limits is worsening traffic and that low-speed streets increase pollution. Key concerns raised include the capacity of road design for low-speed streets, lack of spaces for pedestrians and cyclists, lack of information on existing road rules, and trustworthiness of traffic enforcers. The results were presented to the local government and stakeholders, wherein the following suggested next steps were co-created: targeted information and education campaigns, incorporation of engineering solutions in traffic management, further training of enforcers, and exploration of contactless enforcement.
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Acknowledgements
The researchers would like to acknowledge Makati Business Club and Konrad Adenauer Stiftung’s Digital Democracy Project, the platform which allowed the researchers to participate in the citizen assemblies and collect and analyze feedback data. The researchers would also like to acknowledge the open and progressive Pasig City for actively engaging their constituents to be part of community building and being responsive to their feedback. And finally, the researchers would like to thank Layertech Labs’ Cloud City Project, supported by Feedback Labs: Feedback Tools Accelerator 2021 grant, which allowed the researchers to collect, analyze, and use citizen feedback to inform decision-making and policymaking of local government units in the Philippines.
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Sangil, M.J., Maceda, L.L. (2023). Citizen Feedback Analytics for Inclusive Policy Design and Decision-making: A Case Study on the Implementation of Low-speed Streets. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Seventh International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 465. Springer, Singapore. https://doi.org/10.1007/978-981-19-2397-5_29
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