Leadership and Global Energy Security: Sentiment Analysis of Twitter Using a Named Entity Recognition

Svitlana Kolosok (), Olena Chygryn () and Svitlana Onyshchenko
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Svitlana Kolosok: Sumy State University
Olena Chygryn: Sumy State University
Svitlana Onyshchenko: National University “Yuri Kondratyuk Poltava Polytechnic”

Chapter Chapter 25 in Leadership, Entrepreneurship and Sustainable Development Post COVID-19, 2023, pp 361-375 from Springer

Abstract: Abstract Awareness of public attitudes toward the components of global energy security is essential to shaping future energy policy, implementing effective energy leadership, and ensuring sustainable development. This chapter explored the latest public opinion on energy security using data from Twitter. We applied the hashtag #energysecurity to filter 981 messages from January to March 2022. According to opinion mining in tweets, most messages were positive, not negative or neutral. Our study used neural networks for named entity recognition with machine learning based on the spaCy software library in Python to classify important energy security issues of public interest. The public was mostly concerned about gas security and less about oil and nuclear security. Many tweets have expressed worry that Russia’s war on Ukraine will increase oil and gas shortages even without sanctions. Leaders seeking public support should consider energy investments in underground gas storage, energy self-sufficiency, and clean energy deployment in the near future.

Keywords: Energy leadership; Twitter; Social media; Energy security (search for similar items in EconPapers)
JEL-codes: L82 N7 Q4 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-28131-0_25

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DOI: 10.1007/978-3-031-28131-0_25

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