Blockchain technology is increasingly finding its way into application areas as it offers major improvements in efficiency, security, and transparency in a wide range of activities. Among others, blockchain has enormous potential for influence in the energy sector, particularly in the field of renewable energy. This paper analyzes the most interesting applications of this technology in the energy sector from the topics most discussed on technical forums. Specifically, this study seeks to identify and examine the most discussed topics through a topic analysis on a dataset of articles extracted from CoinDesk. It is proposed, from these texts, to identify important topics related to energy markets, energy communities, energy traceability, and energy certification. The results were obtained using a Bidirectional Encoder Representations from Transformers (BERT) model for deep topic analysis. BERT provides detailed insight into blockchain technology and renewable energy discussions using natural language processing to extract latent topics and trends. This research attempts to contribute to the existing knowledge set by offering a systematic analysis of the most important topics in the application of blockchain to the energy sector. The results of this study can help technologists identify the interests of the community and foster progress in integrating blockchain into the renewable energy paradigm.
Topics Analysis and Trends on Blockchain Applications in the Energy Sector
Vaccargiu, Matteo;Ibba, Giacomo;Pinna, Andrea
2024-01-01
Abstract
Blockchain technology is increasingly finding its way into application areas as it offers major improvements in efficiency, security, and transparency in a wide range of activities. Among others, blockchain has enormous potential for influence in the energy sector, particularly in the field of renewable energy. This paper analyzes the most interesting applications of this technology in the energy sector from the topics most discussed on technical forums. Specifically, this study seeks to identify and examine the most discussed topics through a topic analysis on a dataset of articles extracted from CoinDesk. It is proposed, from these texts, to identify important topics related to energy markets, energy communities, energy traceability, and energy certification. The results were obtained using a Bidirectional Encoder Representations from Transformers (BERT) model for deep topic analysis. BERT provides detailed insight into blockchain technology and renewable energy discussions using natural language processing to extract latent topics and trends. This research attempts to contribute to the existing knowledge set by offering a systematic analysis of the most important topics in the application of blockchain to the energy sector. The results of this study can help technologists identify the interests of the community and foster progress in integrating blockchain into the renewable energy paradigm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.