Discover the emotion expressed in a text
Emotions are of paramount importance in people's lives, and greatly influence their perceptions and thoughts. MeaningCloud’s Emotion Recognition Pack allows to detect basic emotions expressed in all types of unstructured content (surveys, social comments, contact center interactions) according to a model based on well-known Plutchik’s Wheel of Emotions.
Text Analytics for Emotion Recognition
Emotions play a prominent role in the individual and social life of people and have a great impact on their behavior and judgment. MeaningCloud’s Emotion Recognition Pack applies advanced text analytics to identify emotions that are explicitly expressed in all types of unstructured content. Using Emotion Recognition you can easily and quickly analyze thousands of messages in surveys, social networks, review sites, contact center interactions and extract that information that will let you know how your customers or employees feel or take the emotional pulse of your market or society.
The Emotion Recognition Pack is based on Robert Plutchik's Wheel of Emotions, a psycho-evolutionary classification approach for general emotional responses. Plutchik considered that there are eight of those primary responses, distributed in pairs of opposite emotions, and that they are triggers of behaviors with high survival value.
A model for recognizing emotions
MeaningCloud’s Emotion Recognition Pack is implemented as a granular categorization model that allows the identification of the following emotions, explicitly expressed in the text:
- Joy: happiness, pleasure.
- Sadness: grief, unhappiness.
- Anger: rage, annoyance.
- Fear: alarm, terror.
- Confidence: security, decision.
- Disgust: repulsion, aversion.
- Anticipation: foresight, expectation.
- Surprise: amazement, astonishment.
This model runs on our Deep Categorization API, which is based on MeaningCloud’s powerful morphosyntactic and semantic analysis.
Benefits of emotion recognition
The Emotion Recognition Pack allows you to detect basic emotions and add value in a wide range of scenarios:
Social media
Analyze comments on social networks, forums and review sites to detect the emotional response of people (customers, employees, etc.) about your products and organization and prevent reputational crises.
Surveys and CX management systems
Interpret unstructured feedback to detect the emotional bonding of customers with your company and discover positive and negative drivers.
Contact center
Analyze interactions in the contact center from the emotional point of view to route, respond and treat them optimally.
Chatbots
Give your conversational bots a more human quality, giving them the possibility of taking into account the emotional dimension of visitor expressions.
Content publishing
Guarantee the objectivity and quality of your content, detecting inappropriate emotional signals.
Complement it with other MeaningCloud functions
The Emotion Recognition Pack can be combined with other MeaningCloud features and products to gain a deep understanding of your users, customers, employees and other stakeholders:
Sentiment Analysis API
It determines the positive / negative / neutral polarity of what is expressed, both at the whole document level and associated to aspects or attributes (entities, concepts) that appear in the text.
Intention Analysis Pack
It identifies the stage in a customer journey (Information, Advice, Purchase, Support, Recommendation, Complaint, Cancellation) expressed in a text.
Voice of the Customer Analysis Pack
It analyzes customers' unstructured feedback according to different dimensions: product, service, quality, satisfaction…
Voice of the Employee Analysis Pack
It analyzes employees’ unstructured feedback according to various axes: organization, skills, satisfaction…
The combination of Sentiment, Emotion, Intention and VoC / VoE analysis provides a 360º vision with high predictive value of the opinions, attitudes and behaviors of your organization’s most important stakeholders.
