Our team collaborated with the Mood Index of Online Social Indicators team to create a game-changing mood classifier for AI. We developed metrics to prove mood has social connectivity and can be computed.
Mood Index of Leading Online Sociability Indicators
Our team developed metrics for a mood classifier. Our goal was to prove that mood has social connectivity on the internet that could be computed regularly-and hence, at least semi-automatically-and distributed widely. During this doctoral seminar, our team developed metrics for a mood classifier. By collecting vast amounts of Twitter and Facebook feeds, we were successful in classifying several types of moods, like sarcasm and sadness.
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.