Analysis of Customer Sentiment on Product Features After the Outbreak of Coronavirus Disease (Covid-19) Based on Online Reviews

Abstract

The outbreak of the coronavirus disease not only caused many deaths worldwide but also severely affected the development of the global economy, such as supply chain disruptions, plummeted demand, unemployment, etc. These social changes have led to changes in customers' purchasing patterns. Therefore, it is more important than ever for manufacturers to quickly identify and respond to changing customer purchasing patterns and requirements. However, few studies have been done on dynamic changes in customer preferences for product features following COVID-19 spread. This study aims to investigate the dynamic change of customer sentiment on product features following COVID-19 through sentiment analysis based on online reviews. The proposed methodology consists of two main processes: feature extraction and sentiment analysis. After finding a specific feature of the product through feature extraction, the words used to mention the feature in the review were analyzed for sentiment analysis of customers. To demonstrate the methodology, a case study is conducted using new and refurbished smartphone reviews to investigate the dynamic changes in customer sentiment during COVID-19.

Eye-tracking study of public acceptance of 5G base stations in the context of the COVID-19 pandemic

“…In addition, individual subjective perception (Shimojo et al, 2003), emotional preference, cognitive process (Guo et al, 2022) and so on can also be predicted through data such as eye tracking and fixation time. With the rapid development of the internet, user-generated content on social media has become an important mode of promoting information interaction in the process of public participation (Kim et al, 2021). Online reviews are a representative form of Internet content created by users on social media (Jabr and Zheng, 2014), and the information it contains is an important resource for the public to browse and consider before making relevant decisions (Benbasat, 2006).…”

“…Social media have gradually become the main channel for the public to obtain information. The public shares their views, experiences and views through social media to discuss and obtain information (Kim et al, 2021). In particular, during the COVID-19 epidemic, social media became the main communication pathway owing to the need for quarantine.…”

“…, 2022) and so on can also be predicted through data such as eye tracking and fixation time. With the rapid development of the internet, user-generated content on social media has become an important mode of promoting information interaction in the process of public participation (Kim et al. , 2021).…”

Differentiating online products using customer perceptions of sustainability

“…The scholars extracted 10 features for laptops, nine for wearable devices and eight for smartphones. Kim, Park & Kim (2021) build on the above method by applying it to investigate the role of COVID-19 pandemic in changing customer preferences. The scholars collected 8548 reviews for smartphones dating before the pandemic and 7263 reviews for smartphones dating after the pandemic began.…”

Public’s Sentiment Analysis on Shopee-Food Service Using Lexicon-Based and Support Vector Machine

“…Therefore needed a way to analyze it, called sentiment analysis. Sentiment analysis is one of the Natural Processing Language (NLP) sectors, focusing on determining human traits on a topic or polarity score from a text (Jinju, Seyoung, & Harrison, 2021). The research object of sentiment analysis is determining accuracy from a text (Jiménez-Zafra, Cruz-Díaz, Taboada, & Martín-Valdivia, 2021).…”