August 24, 2016 | Written by: Alexis Plair
Categorized: Watson | What's New
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“Many in the field of Cognitive AI research and development speak of the importance of context. Context could be visualized similar to that of an onion, with multiple levels of nested, related and non-related context. But perhaps one of the most important layers is Emotional context, as it has the power to transform dynamic decision making internal to the intelligence.”
—Brennon Williams, Chief Executive Officer & Founder of Iridium Systems and Robotics Corporation
On July 1st, 2016, the Emotion Analysis capability in AlchemyLanguage became Generally Available for production use. Now, with our latest updates, you can use Sentiment & Emotion Analysis to understand social data at a deeper level than ever before.
AlchemyLanguage users take their Sentiment Analysis one step deeper to detect five distinct emotions in text – joy, fear, sadness, anger, and disgust. Users employ our sentiment and emotion capabilities to discover emotional trends in social media, prioritize inbound social data, and more.
Now, our customers can get even more granular and accurate with the Emotion Analysis API. Part of what makes our Sentiment Analysis API special is the fact that users can detect sentiment for user-specified phrases, entities and keywords. Now, with our latest update, the Emotion Analysis API can detect emotions towards a user-specified phrase, entity or keyword as well.
Try the new features in the AlchemyLanguage Demo
We thank all of our users for the consistent feedback that has driven these product updates. As we continue to grow and enhance our capabilities, we appreciate your support.