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A New Sentiment Analysis System of Climate Change for Smart City Governance Based on Deep Learning

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Innovations in Smart Cities Applications Volume 4 (SCA 2020)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 183))

Abstract

With the world’s massive population growth, governments over the world are trying to move closer to their citizens, in order to improve the management and governance of their cities, and made it smarter than ever before. Smart city technologies are used to analyze and evaluate huge volumes of data to monitor city dwellers, for better governance. Moreover, social media can be a useful vehicle for governments to better understand their citizens. Twitter sentiment analysis is a great approach to provide deep insight into how citizens behave towards phenomena and thus has definite use for smart city governance and monitoring. Climate change is a critical phenomenon. In recent years, the existence of climate change or global warming became an increasingly public debate. In this paper we developed a deep learning model. Based on convolutional Neural Network (CNN) in order to identify believers and deniers of the climate change phenomenon. And we examined the temporal patterns of climate change discussions on Twitter and its driving factors. Results demonstrate that the developed CNN model successfully identified citizens behavior towards climate change with an overall accuracy of 97% denier and 91% believer. Our model provides improved understanding of factors affecting citizen attitudes on climate change, as an efficient tool for smart city monitoring and governance.

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Author information

Authors and Affiliations

  1. Faculty of Science and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Mustapha Lydiri & Yousef El Mourabit

  2. IGDR, UMR 6290 - CNRS - Rennes 1 University, Rennes, France

    Youssef El Habouz

Authors
  1. Mustapha Lydiri
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  2. Yousef El Mourabit
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  3. Youssef El Habouz
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Corresponding author

Correspondence to Mustapha Lydiri .

Editor information

Editors and Affiliations

  1. Computer Engineering Department, Faculty of Sciences and Techniques, Tangier, Morocco

    Mohamed Ben Ahmed

  2. Computer Engineering Department, Faculty of Engineering, KarabĂĽk University, KarabĂĽk, Turkey

    İsmail Rakıp Karaș

  3. CICS.NOVA - Interdisciplinary Centre of Social Sciences, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal

    Domingos Santos

  4. Department of Sociology of Culture and Communication, Saint Petersburg State University, St. Petersburg, Russia

    Olga Sergeyeva

  5. Faculty of Sciences and Techniques, Association Méditerranéenne des Sciences et Technologies, Tangier, Morocco

    Anouar Abdelhakim Boudhir

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Lydiri, M., El Mourabit, Y., El Habouz, Y. (2021). A New Sentiment Analysis System of Climate Change for Smart City Governance Based on Deep Learning. In: Ben Ahmed, M., Rakıp Karaș, İ., Santos, D., Sergeyeva, O., Boudhir, A.A. (eds) Innovations in Smart Cities Applications Volume 4. SCA 2020. Lecture Notes in Networks and Systems, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-030-66840-2_2

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  • DOI: https://doi.org/10.1007/978-3-030-66840-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66839-6

  • Online ISBN: 978-3-030-66840-2

  • eBook Packages: EngineeringEngineering (R0)

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