Affiliation:
1. Sharda University, India
Abstract
In today's digitally interconnected world, customer feedback has become a goldmine of valuable information for businesses seeking to improve their products, services, and overall customer experience. Analysing this data is instrumental in boosting business. Machine learning and sentiment analysis have emerged as powerful tools in processing and extracting valuable insights from customer feedback. MonkeyLearn, Lexalytics are some of the sentiment analysis tools which are well suited for processing customer feedback. Sentiment analysis powered by machine learning algorithms automates the process of extracting insights from unstructured textual data. This chapter will explore the underlying principles of machine learning algorithms and their roles in automating sentiment analysis from diverse sources such as online reviews, social media, surveys, and customer support interactions. Through real-world case studies and practical examples, readers will discover how to harness the power of sentiment analysis to gain actionable insights and effectively measure customer satisfaction.
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