Positive. Negative. Neutral.
Traditionally, sentiment analysis has consisted of identifying positive and negative sentiments in data –- i.e., thumbs up or thumbs down… However, even promoters have criticisms. All the customers’ intricate feelings are lost using traditional text analysis solutions, which gloss over complex expressions of human emotion, thereby missing valuable business insights.
Luminoso captures the full spectrum of human emotion. That’s why we do emotion analysis.
Luminoso Analytics allows you to quickly discover, and distinguish between nuanced emotions in natural language in order to quickly gain a truer understanding of people’s real needs and wants.
Let’s say a consumer takes the time to write a complex 500-word product review -- some things he likes about the product, other things not so much. His review is then analyzed by traditional “sentiment analysis” methods and boiled down to only one of three simple categories (positive, neutral or negative).
With Luminoso, you can understand your customers’ whole voice and spotlight wins quickly. Luminoso Analytics allows you to evaluate the entire range of your customers’ multifaceted perceptions so that you can provide them with smarter, more targeted solutions.
For example, we often see the terms frustrated and disappointed across different data sets. Luminoso makes a distinction between these discrete emotions and allows you to quickly distinguish what, exactly, each emotional term is related to, as well as how strong those associations are.
What do we mean? People are often frustrated with a feature or function that isn’t working properly. But they can be disappointed in a product that lacks a feature in the first place. The differences we see in associations between those two terms is striking and consistent across data sets. Many expressions of (especially negative) emotion can lead to specific, actionable nuances. These important insights are quickly visible and measurable in Luminoso.
Our software’s ability to discern complex and differentiated feelings, reactions, and sensations, as well as measure their associations against any other concept, is why we refer to Emotion Analysis.
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