This model is created with the intent of classifying positive or negative sentiment in any consumer conversation.
Positive | : We hope all of your consumers are happy! A positive label indicates that consumers express their happiness, satisfaction, trust or gratitude. |
Negative | : Well, it's impossible to make everyone happy, right? A negative label indicates conversations that consumers express their dissatisfaction, rage, disappointment or simply sadness. |
English , Portuguese , French , Turkish
Nowadays, most people in the marketing and research world are familiar with social media monitoring, brand monitoring, the voice of the customer, customer service, and market research. With all these terms, sentiment analysis shines and becomes a game-changer that provides an essential insight into consumers' thoughts and feelings. This model allows you to get more meaningful analysis by classifying a wide range of conversations as "positive", "negative" or "neutral", from the banking industry to B2C products, from the film industry to the automotive world. It means less manual work for marketing professionals and more time to take action.
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Designed for marketing and research professionals. No programming skills are required.
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