A wealth of unstructured opinion data exists online today. Every day, millions of consumers express their views and opinions regarding products and services. These opinions are subjective information that represents the user’s sentiments, feelings, or appraisal related to the same. Though volunteered, it contains the raw, unsolicited views and opinions about a brand, individual, or event. Using this information product reviews, social media posts, and discussion forums, businesses can identify trends in customer sentiment, find what drives customer satisfaction, and react to negative feedback. The challenge is of analyzing and making sense of this data at scale. Natural Language Processing (NLP), and specifically Sentiment Analysis, provides an automated way to categorize this feedback into positive, neutral, and negative categories. Opinion Mining can add greater depth to the understanding of customer sentiment and provide a more granular view of the data in the voice of the customer. Join me as we discuss the science of using text analysis to understand the drivers of public sentiment, using the latest innovations from Azure AI.
Liji is a technophile with over a decade's industry experience in technical and leadership roles. As Manager (Modern Application Development) at Valorem Reply, she leads a team of digital transformation consultants. She's passionate about emerging technologies, particularly building AI-powered (delightful) experiences for a global clientele.
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