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01.12.2023 | Original Article

Public sentiment toward renewable energy in Morocco: opinion mining using a rule-based approach

verfasst von: Mohammed Kasri, Anas El-Ansari, Mohamed El Fissaoui, Badreddine Cherkaoui, Marouane Birjali, Abderrahim Beni-Hssane

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2023

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Abstract

Morocco’s goal is to reach 52% of the energy mix by 2030. However, Moroccans’ acceptance and support for renewable energy are important to accelerate renewable deployment and increase the share of renewables in the total power capacity. To the best of our knowledge, this work is the first study in the Middle East and North Africa region that addresses people’s opinions on renewable energy using a natural language processing technique called sentiment analysis. The process started by collecting Moroccan’s comments on renewable energy during the past 10 years. After preprocessing, we identified the polarity (positive or negative) of each comment by applying one of the sentiment analysis approaches, namely a rule-based approach. As a result, Moroccans do not show a high positive sentiment toward renewables, which means there is a need for more public awareness. Further, Moroccans show more attention to wind and solar energy than other types of renewables because of the naturally available resources. In terms of energy policy, the public indicates that the Moroccan government focuses on big projects and does not encourage energy self-sufficiency. As a powerhouse in this domain, Morocco may consider educating and encouraging people to use renewables in order to win more support for clean energy, reduce its energy dependency, and help the growth of the renewables business.

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Titel: Public sentiment toward renewable energy in Morocco: opinion mining using a rule-based approach
verfasst von: Mohammed Kasri
Anas El-Ansari
Mohamed El Fissaoui
Badreddine Cherkaoui
Marouane Birjali
Abderrahim Beni-Hssane
Publikationsdatum: 01.12.2023
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2023
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-023-01119-3

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