Human text contains a vast array of sentiments that convey emotion, tonality, values, principles, and other affective states. While the complexities of sentiments were only interpretable by the human brain, modern AIs are capable of unraveling affective states at scale.
Sentiment and NLP text analysis is helping organizations understand the sentiments behind their brands and products, also enabling them to manage their reputations.
NLP sentiment analysis techniques enable businesses and organizations to make sense of complex textual data. NLP models are trained on sentiment analysis datasets to instruct them on how to parse and understand text's emotional or affective qualities.
For example, social media sentiments encapsulate everything from cultural ideas, norms, and knowledge to brand sentiments. Twitter data analysis enables brands to home in on emerging trends and customer feedback. Through customer sentiment analysis, organizations can analyze everything from customer service chat logs to feedback forms to uncover insights into brands, products, and concepts at scale.
Sentiment analysis AI is trained using NLP techniques, including tagging and labeling sentiments to instruct the AI whether tones or emotions are broadly positive, negative, or neutral, though it is possible to uncover finer layers of meaning.
Aya Data’s sentiment analysis services enable your business or organization to extract complex meaning from human text. Our data experts are excellent linguists in their own right and can work in English, French, and over 10 African dialects.
We will help you train accurate NLP models that utilize sentiment and content analysis to drill down into what text means on a higher emotional level.