Data-Driven Decision Making with Sentiment Analysis in R | by Devashree Madhugiri | Jan, 2025


Leveraging the Quanteda, Textstem and Sentimentr Packages to Extract Customer Insights and Enhance Business Strategy

Towards Data Science

13 min read

14 hours ago

Image by Ralf Ruppert from Pixabay

In a rapidly evolving world that is getting more and more AI-driven every instant, businesses now need to constantly seek a competitive edge to remain sustainable. Companies may do this by regularly observing and analyzing customer opinions regarding their products and services. They achieve this by assessing comments from many sources, both online and offline. Identifying positive and negative trends in customer feedback allows them to fine-tune product features and design marketing strategies that meet the needs of customers.

Thus, customer opinions need to be discerned appropriately to find valuable insights that can help make informed business decisions.

Sentiment analysis, a part of natural language processing (NLP), is a popular technique today because it studies people’s opinions, sentiments, and emotions in any given text. Businesses can understand public opinion, monitor brand…

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