Abstract
Optimising general waste management and collection has been shown to minimise the health hazards from overfilled garbage containers and pollution from heavy trucks collecting waste. Smart cities and the public would reap the great benefits of finding a solution to optimise the waste collection system and general waste management. Therefore, this paper proposes a solution to gather citizen waste critics from Twitter as a data source and analyse the outcome. Firstly, the paper presents the related work, framework and method. After that, analyse the data and discuss the result. The results show barriers in both collection and content of the data as it contains a lot of false data. The main contribution will therefore be a foundation for further research and experiment of data collection and analysis.
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Acknowledgements
This work has been supported by the projects TED2021-130890B, funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR, and Ramon y Cajal Grant RYC2018-025580-I, funded by MCIN/AEI/10.13039/501100011033, “FSE invest in your future” and “ERDF A way of making Europe”.
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Junge, P., Stavrum-Tång, S., Cecilia, J.M., Poza-Lujan, JL. (2023). Using Data Analytic for Social Media Posts to Optimise Recyclable Solid Waste Management Exemplary at the City of Valencia. In: Ossowski, S., Sitek, P., Analide, C., Marreiros, G., Chamoso, P., Rodríguez, S. (eds) Distributed Computing and Artificial Intelligence, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-031-38333-5_11
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DOI: https://doi.org/10.1007/978-3-031-38333-5_11
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