Sentiment Analysis of Online Shopping based on Twitter and RStudio - Vega Barrios, Alejandra (HITOS DE CIENCIAS ECONÓMICO ADMINISTRATIVAS, 2023)
OBJECTIVE: Identify opinions about online purchases in the period from April 25th to May 16th, 2022. MATERIAL AND METHOD: The approach of this study is non-experimental, qualitative, through grounded theory, using the sentiment analysis technique to classify unstructured information in structured data of a text fragment as positive sentiment (> 0), negative (< 0) or neutral (0), based on tweets from the social network Twitter about #comprasenline; RStudio software was used for data processing. RESULTS: They show that 50.9% of users perceive negative sentiment toward online purchases, while 40.8% consider online purchases positive. CONCLUSIONS: The impact of the phenomenon of online shopping, despite being a new form of consumption and purchasing habit, is still not so accepted, since feelings or opinions continue to be judged about the security and guarantee of the supply, which must be counteracted by marketing strategies to encourage online purchases and the security provided by making them correctly.