Sentiment analysis on the brand recall of twitter data with the tool of NCSU tweet sentiment visualization

Abstract

Social media have gained increased attention in recent years. Social networking platforms are commonly utilised to share and spread opinions on a wide range of subjects, both publicly and privately. Twitter is a social networking platform that is becoming more and more popular. Businesses now have a rapid and effective way to study client opinions on topics that are essential to their marketability via Twitter. A method to computationally measuring customer perceptions is to create a programme for sentiment analysis. This study presents the concept of a sentiment analysis that extracts sentiment from a sizable number of tweets. The results divide consumers' opinions of brand memory via tweets into two categories: pleasant and unpleasant, which are depicted in a matrix and affinity diagram. The research did intend to determine consumer perceptions of brand recall, but due to NCSU's limitations regarding the data that can be pulled from Twitter; this approach will need to be used in conjunction with other social media and e-commerce platforms going forward.