Development and Application of a Big Data Analysis-Based Procedure to Identify Concerns about Renewable Energy

So-Yun Jeong, Jae-Wook Kim, Han-Young Joo, Young-Seo Kim and Joo-Hyun Moon
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So-Yun Jeong: Department of Energy Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan-si 31116, Chungnam, Korea
Jae-Wook Kim: Department of Energy Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan-si 31116, Chungnam, Korea
Han-Young Joo: Department of Energy Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan-si 31116, Chungnam, Korea
Young-Seo Kim: Department of Energy Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan-si 31116, Chungnam, Korea
Joo-Hyun Moon: Department of Energy Engineering, Dankook University, 119, Dandae-ro, Dongnam-gu, Cheonan-si 31116, Chungnam, Korea

Energies, 2021, vol. 14, issue 16, 1-13

Abstract: To achieve carbon neutrality by 2050, Korea has been expanding its investment in renewal energy distribution and technology development. However, with this rapid expansion of renewable energy, public concern about it has grown. This study developed and used a big data analysis-based procedure to analyze the questions registered on Naver, the largest portal site in Korea, from 2008 to 2020 to identify public concern over renewable energy. The big data analysis-based procedure consisted of two steps. The first was a frequency analysis to identify the most frequently registered words. The second was to classify questions using term frequency-inverse document frequency (TF-IDF) weight and cosine similarity based on word2vec. The analysis revealed the most frequently registered words related to renewable energy, such as “solar power,” “power generation,” “energy,” and “wind power.” It also revealed the most frequently registered questions, such as those related to solar panel installation, renewable energy generation methods, and certificates. To continue expanding renewable energy, it is becoming increasingly important to understand the public’s concerns and create a method to resolve their objections to renewable energy. It is expected that the procedure in this study may provide relevant insight for the method.

Keywords: carbon neutrality; renewable energy; public concerns; big data; frequency analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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