Understand the social sentiment of your brand, product or service while monitoring online conversations. Sentiment Analysis is contextual mining of text which identifies and extracts subjective information in source material.

Sentiment analysis API provides a very accurate analysis of the overall emotion of the text content incorporated from sources like Blogs, Articles, forums, consumer reviews, surveys, twitter etc. Sentiment Analysis can be widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service.

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Sentiment Analysis

It uses Long Short Term Memory (LSTM) algorithms to classify a text blob's sentiment into positive and negative. LSTMs model sentences as chain of forget-remember decisions based on context. It is trained on social media data and news data differently for handling casual and formal language. We also have trained this algorithm for various custom datasets for different clients.

The “state-of-the-art” augmentation techniques include seven augmenters. These are Character augmenter,Spelling augmenter, Random word insertion, Random word deletion, Split augmenter,Synoynm augmenter, Similar Word augmenter.