Sentiment Analysis of Online Auction Service Quality on Twitter Data: A case of E-Bay

Abstract

Customer Satisfaction is the most important factor to determine long term success of a company, and that includes Online Auction company. Customer Satisfaction is important for an Online Auction company to enhance its customer loyalty in the middle of today's competition. This research is done to analyze the significant Service Quality of Online Auction, using sentiment analysis in Twitter, by targeting the customers that used online auction E-Bay; one of the largest online auction platform in the world. The data is retrieved from tweets of E-Bay's customer to @Ebay and @askEbay twitter account, before being processed using Lexicon Classification method to generate sentiment analysis for each significant service quality factors. The Results shows that Information Reliability, Interface Design and Security, and Reliability are the factors that gained the most feedback and sentiment from customers.