Metaverse in Investment Using Sentiment Analysis and Machine Learning

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Author(s): Eik Den Yeoh (HELP University, Malaysia), Tinfah Chung (HELP University, Malaysia)and Yuyang Wang (Institute of Automation, Chinese Academy of Sciences, China)
Copyright: 2023
Pages: 36
Source title: Strategies and Opportunities for Technology in the Metaverse World
Source Author(s)/Editor(s): P.C. Lai (University of Malaya, Malaysia)
DOI: 10.4018/978-1-6684-5732-0.ch006

Keywords: Information Science Reference / Media & Communications / Virtual Communities & Virtual Reality / Web Technologies

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Abstract

At the end of 2019, individuals' outdoor activities were restricted due to the emergence of COVID-19. As a result of this phenomenon, interest in online activities and interaction in the metaverse environment has increased. Online games have exploded in popularity with the young generation in Metaverse where they can earn money through the platforms. Thus, it is desirable to investigate emerging technology and analyse how to invest using techniques, such as sentiment analysis and machine learning (ML), to predict crypto trends. This study analysed time series data for crypto price and text, where information like news, articles, and feedback from social media can use the input to generate the sentiment score to understand the crypto trends. FinBERT is a sentiment model that was used for this study to generate the result. The AI investing framework is built to incorporate both sentiment analysis technique and predictive model for this chapter, to address the research questions and enable one to make more informed decisions.

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Metaverse in Investment Using Sentiment Analysis and Machine Learning

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