Crypto-currencies narrated on tweets: a sentiment analysis approach

Abstract

PurposeCrypto-currencies, decentralized electronic currencies systems, denote a radical change in financial exchange and economy environment. Consequently, it would be attractive for designers and policy-makers in this area to make out what social media users think about them on Twitter. The purpose of this study is to investigate the social opinions about different kinds of crypto-currencies and tune the best-customized classification technique to categorize the tweets based on sentiments.Design/methodology/approachThis paper utilized a lexicon-based approach for analyzing the reviews on a wide range of crypto-currencies over Twitter data to measure positive, negative or neutral sentiments; in addition, the end result of sentiments played a training role to train a supervised technique, which can predict the sentiment loading of tweets about the main crypto-currencies.FindingsThe findings further prove that more than 50 per cent of people have positive beliefs about crypto-currencies. Furthermore, this paper confirms that marketers can predict the sentiment of tweets about these crypto-currencies with high accuracy if they use appropriate classification techniques like support vector machine (SVM).Practical implicationsConsidering the growing interest in crypto-currencies (Bitcoin, Cardano, Ethereum, Litcoin and Ripple), the findings of this paper have a remarkable value for enterprises in the financial area to obtain the promised benefits of social media analysis at work. In addition, this paper helps crypto-currencies vendors analyze public opinion in social media platforms. In this sense, the current paper strengthens our understanding of what happens in social media for crypto-currencies.Originality/valueFor managers and decision-makers, this paper suggests that the news and campaign for their crypto in Twitter would affect people’s perspectives in a good manner. Because of this fact, the firms, investing in these crypto-currencies, could apply the social media as a magnifier for their promotional activities. The findings steer the market managers to see social media as a predictor tool, which can analyze the market through understanding the opinions of users of Twitter.