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A BERT-based Approach to Alleviate Civic Tech Tools Overcrowding: A case study of Taiwan's JOIN e-petition system

Published: 11 June 2024 Publication History

Abstract

Online petition systems as a crowd-sourcing and feedback tool offered by public authorities are becoming more and more common these days. The volume of incoming petitions from digital platforms is increasing. Governments typically review petitions in a screening process before they can be posted on an online platform. In order to reduce the burden on public authorities and to provide fast feedback to a petitioner on whether a petition is admissible or not, an automated system is proposed to assistance to the authorities and petitioners alike. The proposed system attempts to classify whether a petition is admissible or not. By applying a BERT-based model to a dataset of petitions submitted to Taiwan’s JOIN platform 2015-2023, the classification model achieve a classification accuracy of 67%. While the model would be improved in future work, the experiments conducted the overall feasibility of the proposed system to alleviate the overcrowding of civic tech tools.

References

[1]
Ayman Alarabiat and Delfina Sá Soares. 2016. Electronic Participation through Social Media. In Proceedings of the 9th International Conference on Theory and Practice of Electronic Governance. ICEGOV, ACM, Montevideo, Uruguay, 191–194. https://doi.org/10.1145/2910019.2910109 Published: 01 March 2016.
[2]
Miguel Arana-Catania, Felix-Anselm Van Lier, Rob Procter, Nataliya Tkachenko, Yulan He, Arkaitz Zubiaga, and Maria Liakata. 2021. Citizen Participation and Machine Learning for a Better Democracy. Digit. Gov.: Res. Pract. 2, 3, Article 27 (jul 2021), 22 pages. https://doi.org/10.1145/3452118
[3]
Miguel Arana-Catania, Felix-Anselm van Lier, Rob Procter, Nataliya Tkachenko, Yulan He, Arkaitz Zubiaga, and Maria Liakata. 2021. Citizen Participation and Machine Learning for a Better Democracy. Digit. Gov.: Res. Pract. 2, 3 (2021), 1–22. https://doi.org/10.1145/3452118
[4]
Taco Brandsen, Trui Steen, and Bram Verschuere. 2018. Co-production and co-creation: Engaging citizens in public services. Taylor & Francis, New York, USA.
[5]
Adrian Bua and Sonia Bussu. 2021. Between governance-driven democratisation and democracy-driven governance: Explaining changes in participatory governance in the case of Barcelona. European Journal of Political Research 60, 3 (2021), 716–737.
[6]
Colin Crouch. 2016. The march towards post-democracy, ten years on. The political quarterly 87, 1 (2016), 71–75.
[7]
Y. Chiu et al.2023. PEPO: Petition Executing Processing Optimizer Based on Natural Language Processing. In 2023 IEEE Position In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, IEEE, New York, NY, USA, 1–5. https://doi.org/10.1145/3393914.3398111
[8]
Xiaodong Feng, Chaorui Wang, and Juan Wang. 2023. Understanding how the expression of online citizen petitions influences the government responses in China: An empirical study with automatic text analytics. Information Processing and Management 60, 3 (2023), 103330. https://doi.org/10.1016/j.ipm.2023.103330 Available online 1 March 2023.
[9]
Brigitte Geissel. 2022. The Future of Self-Governing, Thriving Democracies: Democratic Innovations By, With and For the People (1st ed.). Routledge, EU. https://doi.org/10.4324/9781003297109
[10]
Leonhard Hennen, Ira Van Keulen, Iris Korthagen, Georg Aichholzer, Ralf Lindner, and Rasmus Øjvind Nielsen. 2020. European e-democracy in practice. Springer, Cham.
[11]
Hsin-Ying Huang, Mate Kovacs, Victor Kryssanov, and Uwe Serdült. 2021. Towards a Model of Online Petition Signing Dynamics on the Join Platform in Taiwan. In 2021 Eighth International Conference on eDemocracy & eGovernment (ICEDEG). IEEE, IEEE, Quito, Ecuador, 28-30 July 2021, 199–204. https://doi.org/10.1109/ICEDEG52154.2021.9530852
[12]
Marijn Janssen and Maria A Wimmer. 2015. NUMER. Policy practice and digital science: Integrating complex systems, social simulation and public administration in policy research 10 (2015), 1–14.
[13]
Pascal Jürgens and Andreas Jungherr. 2010. The Political Click: Political Participation through E-Petitions in Germany. Policy & Internet 2, 4 (2010), 131 – 165.
[14]
I. Kumpulainen and J. Vankka. 2021. BERT-fused Model for Finnish-Swedish Translation. In 2021 Eighth International Conference on Social Network Analysis, Management and Security (SNAMS). IEEE, Gandia, Spain, 1–4. https://doi.org/10.1109/SNAMS53716.2021.9731849
[15]
Hélène Landemore. 2020. Open democracy: Reinventing popular rule for the twenty-first century. Princeton University Press, Princeton.
[16]
Ying Li, Wensi Fang, Hang Sun, Xiangyu Liu, Wei Du, Yijun Liu, and Qianqian Li. 2023. PecidRL: Petition expectation correction and identification based on deep reinforcement learning. Information Processing and Management 60, 3 (2023), 103285. https://doi.org/10.1016/j.ipm.2023.103285 Available online 27 January 2023.
[17]
Silvia Lips, Rozha K. Ahmed, Khayyam Zulfigarzada, Robert Krimmer, and Dirk Draheim. 2021. Digital Sovereignty and Participation in an Autocratic State: Designing an e-Petition System for Developing Countries. In DG.O2021: The 22nd Annual International Conference on Digital Government. ACM, Omaha, NE, USA, Article 27. https://doi.org/10.1145/3463677.3463706
[18]
Youyao Liu, Haimie Huang, Jialei Gao, and Shihao Gai. 2021. A study of Chinese Text Classification based on a new type of BERT pre-training. In 2021 34th International Conference on Neural Information Processing (ICONIP). IEEE, Guangzhou, China, 303–306. https://doi.org/10.1109/ICONIP53518.2021.00062
[19]
Alois Paulin. 2020. An overview of ten years of liquid democracy research. In The 21st Annual International Conference on Digital Government Research. IEEE, New York, NY, USA, 116–121.
[20]
Tiago Peixoto, Fredrik M. Sjoberg, and Jonathan Mellon. 2020. A Get-Out-the-Vote Experiment on the World’s Largest Participatory Budgeting Vote in Brazil. British Journal of Political Science 50, 1 (2020), 381–389. https://doi.org/10.1017/S0007123417000412
[21]
Uwe Serdült, Fernando Mendez, Maja Harris, and Hyeon Su Seo. 2016. Scaling Up Democracy with E-Collection?. In CeDem 2016 Conference for E-Democracy and Open Government 2015 (18-20 May), Noella Edelmann and Peter Parycek (Eds.). IEEE, Danube University Krems, Austria, 25–31. https://doi.org/10.1109/CeDEM.2016.13
[22]
Anthony Simonofski, Jerome Fink, and Corentin Burnay. 2021. Supporting policy-making with social media and e-participation platforms data: A policy analytics framework. Government Information Quarterly 38, 3 (2021), 101590.
[23]
Gabriela Viale Pereira, Maria Alexandra Cunha, Thomas J Lampoltshammer, Peter Parycek, and Maurício Gregianin Testa. 2017. Increasing collaboration and participation in smart city governance: A cross-case analysis of smart city initiatives. Information Technology for Development 23, 3 (2017), 526–553.
[24]
Y. Wang, H. Huang, and Y. Xia. 2022. Improving Multi-model Hybrid Chinese Long-text Classification through BERT Optimisation. In 2022 IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE, Shanghai, China, 1–6. https://doi.org/10.1109/ICNSC55942.2022.10004130
[25]
Zekun Yang and Juan Feng. 2023. Explainable multi-task convolutional neural network framework for electronic petition tag recommendation. Electronic Commerce Research and Applications 59 (2023), 101263. https://doi.org/10.1016/j.elerap.2023.101263
[26]
B. Yu, C. Deng, and L. Bu. 2022. Policy Text Classification Algorithm Based on BERT. In 2022 11th International Conference of Information and Communication Technology (ICTech). IEEE, Wuhan, 488–491. https://doi.org/10.1109/ICTech55460.2022.00103

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    dg.o '24: Proceedings of the 25th Annual International Conference on Digital Government Research
    June 2024
    1089 pages
    ISBN:9798400709883
    DOI:10.1145/3657054
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    Published: 11 June 2024

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    Author Tags

    1. civic tech
    2. crowd-sourcing
    3. digital governance systems
    4. e-petition
    5. machine learning
    6. online petition

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