This study focuses on analysing brand-related tweets associated with five leading UK online retailers during the most important sales period of the year.
This study focuses on analysing brand-related tweets associated with five leading UK online retailers during the most important sales period of the year.
We explore trends in customer tweets by utilising a combination of data analytics approaches including time series analysis, sentiment analysis and topic ...
Through the sentiment and time series analyses, we identify several critical time points that lead to significant deviations in sentiment trends. We then use a ...
Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media ; Number of pages, 14 ; Journal, Computers in Human Behavior.
Decoding the Sentiment Dynamics of Online Retailing Customers: Time Series Analysis of Social Media by Noor Farizah Ibrahim, Xiaojun Wang published.
Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media · Noor Farizah IbrahimXiaojun Wang. Business, Computer ...
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The purpose of this study is to identify the customers' primary topics of concern regarding online retail brands that are shared among Twitter users.
Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media. NF Ibrahim, X Wang. Computers in Human Behavior 96, 32-45, ...
“User-generated content is a valuable source for understanding online shoppers' emotions. Using text-mining techniques, this study identifies seven topics ...