The S1 730 Doctoral Class team proved moods can be computed using metrics based on social media data. This relevant breakthrough is the future of NLP.

 

NATURAL

LANGUAGE PROCESSING

 
 
 
 

NLP

 
 
 
 
 
 

NLP FOR THE FUTURE

 
 
 
 

In a world increasingly enriched by smart technology, AI technologies are increasingly significant in robotics, automotive, manufacturing, law enforcement, disease and pandemic and care prediction. Machine learning markets are expected to reach $117.19 billion by 2027 (Fortune Business Insights, 2020). What does this mean for the future?

 

Mood classifiers and deep learning machine learning algorithms will use a mix of text, speech, and facial recognition to identify and anticipate a wide range of emotions using B2B and B2C IoT devices.

In forensics, robotics, automotive government agencies, and law enforcement, text-based mood classifiers that identify a wide variety of emotions, such as those developed by our S1 730 Doctoral Class Team are extremely valuable.

Large scale social impact.

High financial return. 

 
 

Case Studies