User Sentiment Analysis of Blockchain-Enabled Peer-to-Peer Energy Trading

Title

User Sentiment Analysis of Blockchain-Enabled Peer-to-Peer Energy Trading

Creator

Jain P.; Saxena A.; Mahajan J.; Sing V.P.

Description

A new way for the general public to consume and trade green energy has emerged with the introduction of peer-to-peer (P2P) energy trading platforms. Thus, how the peer-to-peer energy trading platform is designed is crucial to facilitating the trading experience for users. The data mining method will be used in this study to assess the elements affecting the P2P energy trading experience. The Natural Language Processing (NLP) approach will also be used in this study to evaluate the variables that affect the P2P energy trading experience and look at the role of topic modeling in the topic extraction using LDA. The findings show that the general public was more interested in the new technology and how the energy coin payment system operated during the trade process. This explanation of energy as a CC is an outlier that fits well with the conventional literature. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Source

Lecture Notes in Networks and Systems, Vol-726 LNNS, pp. 791-800.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Blockchain; Latent Dirichlet Allocation; Peer-to-Peer energy trading; Sentiment analysis

Coverage

Jain P., Christ University, Pune, India; Saxena A., Christ University, Pune, India; Mahajan J., Christ University, Pune, India; Sing V.P., Energy Exemplar, Pune, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981993715-8

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-99-3716-5_63

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174448035&doi=10.1007%2f978-981-99-3716-5_63&partnerID=40&md5=890b6eb8176eb5926e49e0e3f4851e1d