Building an Emotion Analytics Platform is Easy

In the era where virtually every device is speaking to us through its technological capabilities, we are seeing a rampant rise in a nuanced offering from technology giants. It’s called “Emotions Analytics”- a rather novel innovation in the data science world that leverages Deep Learning and Augmented Intelligence to interact with humans. The importance and value of emotions analytics can be understood from the market proposition that pegs the technology at over $8 Billion for 2021– growing by almost 200% since 2017! Doing a data analytics certification will take you an inch closer to this wonderful universe of Emotion analytics.

Let’s learn more about this unique data science platform.

How the industry defines Emotions Analytics?

According to an independent research company, Emotions Analytics, also referred to as Emotional Analytics (EA) is the specialized branch of deep learning that allows a device, running on AI or Big Data algorithms, to interact with the person based on their mood, behavior, and attitude. From recommending the “Coolest Songs” to play on the music app to switching on the AC as the owner feels the heat — there are various ways a device can turn the technology on its head to interact with humans.

The basic line of thought in understanding EA lies with the way humans interact with technology, product, service, and solutions to make their lives easier.

How EA Works?

Just like how two humans interact with each other, with a piece of basic knowledge about their likes and dislikes, Emotions Analytics also works in a similar fashion. The only difference is that the EA uses an intelligent data analytics platform to collect data from the user and turn it into useful information that can be used to interact based on intent, mood, and behavior.

The best companies that have put EA to good use are Facebook, Google, IBM, Amazon Alexa, Spotify, YouTube, Instagram, and Twitter.

How to build an EA Platform?

While it took Facebook 10 years to build an EA platform, you can do it within a year! Yes, that’s the power of getting a Data Analytics certification that teaches you to be on top of top trends and technologies in the cognitive science industry.

In order to build an EA platform, you need a truckload of labeled data that is ingested from emotionally active human users who provide data in the form of text, video, images, and so on.

The top sources of EA are:

  • Surveys
  • Sample testing
  • Q&A Interviews
  • Facial recognition
  • Video stories
  • Voice

Once labeled data is acquired, an advanced Machine Learning algorithm scours through the data to analyze speech, tone, mood, and expressions. Facial recognition apps analyze facial and eye movements to typically categorize the emotions into 6 categories – hate, anger, smile, confusion, fear, surprise. That’s how the first set of Facebook Reactions came up, do you remember!

Once EA is loaded with ML capabilities, marketing teams use these to populate their best marketing tool – CRMs.

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