Understanding public opinions on social media for financial sentiment analysis using AI-based techniques. Issue 6 (November 2022)

• Record Type: Journal Article
• Authors: Qian, Cheng; Mathur, Nitya; Zakaria, Nor Hidayati; Arora, Rameshwar; Gupta, Vedika; Ali, Mazlan
• Is Part Of: Information processing & management. Volume 59:Issue 6(2022)
• Publication Date: 2022-11
• Subjects: Non-fungible tokens (NFT) -- Emotion analysis -- Sentiment analysis -- Financial trends -- Twitter -- Ethereum; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2022.103098
• Languages: English
• ISSNs: 0306-4573

Abstract

Highlights: Gauged public sentiments on Twitter towards Non-Fungible Tokens·. Provided realistic contradistinction between the NFT market and the traditional financial market. Conducted a secondary trade market analysis to determine reasons for the growing acceptance of NFTs. Established Twitter as a rich research resource for trend analysis of NFTs. Overall, positive sentiment is expressed all over the world regarding NFTs. Anticipation and Trust are predominant emotions, which also drive demand for NFTs. Abstract: The digital currency has taken the financial markets by storm ever since its inception. Academia and industry are focussing on Artificial intelligence (AI) tools and techniques to study and gain an understanding of how businesses can draw insights from the large-scale data available online. As the market is driven by public opinions, and social media today provides an encouraging platform to share ideas and views; organizations and policy-makers could use the natural language processing (NLP) technology of AI to analyze public sentiments. Recently, a new and moderately unconventional instrument known as non-fungible tokens (NFTs) is emerging as an upcoming business market. Unlike the stock market, no precise quantitative parameters exist for the price determination of NFTs. Instead, NFT markets are driven more by public opinion, expectations, the perception of buyers, and the goodwill of creators. This study evaluates human emotions on the social media platforms Twitter posted by the public relating to NFTs. Additionally, this study conducts secondary market analysis to determine the reasons for the growing acceptance of NFTs through sentiment and emotion analysis. We segregate tweets using Pearson Product-Moment Correlation Coefficient (PPMCC) and study 8-scale emotions (Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, and Trust) along with Positive and Negative sentiments. Tweets majorly contained positive sentiment (∼ 72%), and positive emotions like anticipation and trust were found to be predominant all over the world. This is the first of its kind financial and emotional analysis of tweets pertaining to NFTs to the best of our understanding.