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In recent years, the increase of cashless transactions in many countries such as China, Singapore, and Malaysia, are largely due to the rapid development of financial technology and higher consumer confidence on secured money-over-web activities. The adoption rate of fintech products such as eWallet by 21st century young consumers from cash-based to cashless has shifted rather quickly. These young consumers have always been regarded as tech-savvy users of the smartphone era. In Malaysia, 42 eWallet service providers have received official licenses from BNM (Bank Negara Malaysia) and six (6) of them are more popular and widely adopted. They are AEON Wallet, Boost, BigPay, GrabPay, WeChat pay, and Touch‘n Go eWallet (Aji et al., 2020; Karim et al., 2020; Ray, 2017; Upadhayaya, 2012).
The number of digital payment providers increased by leaps and bounds during the COVID-19 pandemic period, as people tried to reduce physical contact with other people. Hence, understanding customers’ needs are extremely important in order to drive business growth, provide better customer services, as well as deeply understanding the strengths and weaknesses of their products. The tech savvy generation, young and old, prefer to express their feelings and opinions on the software or services that they experience on the social media sites. In order to understand the perceptions of digital payment users, sentiment and emotion analysis can be analysed based on users’ reviews, which can be collected from online app stores, such as Playstore or Appstore, social media sites, such as Facebook and Instagram, or product review platforms.
Medhat et al. (2014, p. 1094) defined sentiment analysis as a study of people’s opinions, emotions, and attitudes toward an entity such as individuals, events, and topics. It evaluates the perception of humans towards entities and enables business organizations to employ effective decision-making. Sentiment analysis classifies the sentiment of a text document into three categories, which are: positive, negative, and neutral. For example, “The customer service is so poor! No one replies to me!” is a negative sentiment, and it is important to understand the customers’ reaction towards the products and services they consumed. As a business grows, customer insight is vital, as it provides valuable information to the organization to improve the quality of services and products. In addition, emotion analysis is another dimension of affective analysis that can be conducted to further understand how customers feel based on the reviews collected. Emotion analysis is similar to sentiment analysis, but it is more specific because it classifies the reviews into one or more emotion categories, such as angry and/or happy. There are two emotion models, which are widely used in emotion analysis. Ekman’s six basic emotions (Mohammad & Turney, 2013) contain anger, disgust, fear, happiness, sadness, and surprise emotions. On the other hand, Plutchik’s wheel of emotion (Plutchik, 2003) defines a set of eight emotions, six of the emotion categories were adopted from Ekman, with two additional emotions added: trust and anticipation.