Sentiment Analysis API

About this Cloud Hub Solution:

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In Natural Language Processing, Sentiment Analysis is a technique used to automatically classify text into categories, such as positive, negative, or neutral. While even humans can't agree on 100% of cases due to linguistic ambiguities like sarcasm, state-of-the-art sentiment analysis algorithms trained on thousands of real-life examples can perform on par with humans.

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This API is pre-trained with tens of thousands of examples, carefully classified as positive or negative, eliminating the need for model training. It can also identify text with HTML code and process it without issues.

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Examples

"This restaurant has a lovely atmosphere and the staff is great!" → Positive

‍"Had an awful time at this cafe. Never seen such rude chefs." → Negative‍

"The place was O.K. I really liked the food but the decoration was outdated." → Neutral

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Use Cases

Brands rely heavily on Sentiment Analysis to measure the return on investment (ROI) of their marketing efforts by analyzing social media and customer feedback. Automated sentiment analysis tools help them save time and money, enabling real-time feedback and results analysis.

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Investment companies also use Sentiment Analysis to identify emerging trends and make automated investment decisions by analyzing news articles and sentiment. Thematic analysis can be applied to determine the most discussed features and their corresponding sentiment, allowing brands to track and evaluate customer feedback on specific product features.

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