Sentiment analysis is widely used to supplement the analysis of text data in surveys, complaints, reviews and other customer feedback. In theory, sentiment analysis categorises opinions expressed in a piece of text just as a human might.
However, as the volume and complexity of customer data grows, growing issues with sentiment analysis are providing flawed information and stopping companies from getting the full picture from their data; key customer feedback that could drive positive business change is being missed.
For those who have used sentiment analysis it is likely that you have experienced these inaccuracies from skewed sentiment percentages and incorrect tagging, to completely missing key business insights.
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