AI Series: Demystifying AI in Sentiment Analysis

Carol Feigenbaum |
 03/22/19 |
3 min read

Sentiment analysis is the foundation of social analytics – and of understanding your target audience. But what about new technology like Artificial Intelligence (AI)? Does it really make a big difference? Let’s explore.

Nuance at Scale

As we turn more and more to technology, concern over losing the human touch is legitimate. Interacting with one badly managed chatbot is enough to make anyone question the price of implementing new tech.

Algorithms are great, but don’t they have limitations – particularly when it comes to nuanced conversations? What if they get it wrong, when your brand is banking on those insights?

These are valid concerns. However, the amount of data brands must consider is exactly why algorithms are necessary. They’re the power behind the process – and there’s a lot they need to sort out.

For example, if you want to know where your brand’s logo is showing up on social – and the context of the conversations connected to those images – you need image analytics tools.

In this case, these tools must be able to identify not just your logo, but everything else in the image containing the logo:

  • How it’s being displayed – on an article of clothing, the backdrop of a step-and-repeat, on your product?
  • The demeanor of any people in the photo – are they smiling, laughing, angry?
  • Where the image was taken – this includes both location (i.e., Chicago) and scene recognition (Wrigley Field, Millennium Park, a bakery)

Wrigley Field is tagged, but Apple isn’t – have they noticed their watch in the pic?

If there is text involved this also must be analyzed for sentiment clues by breaking down:

  • Keywords that communicate strong emotion – “love,” “need,” “want,” “obsessed,” “must have,” or “hate,” “can’t stand,” “worst,” “terrible,” etc.
  • Sarcasm/slang – are there words being used to convey opposite emotions than the words mean at face value? Are there pop culture references or slang words that reveal deeper meaning?
  • Emojis – these little graphics are often the emotional “punctuation” of social posts, and might be what best clarifies emotion clouded by sarcasm

The only possible way to sift through the voluminous posts on social is with algorithm-driven technology like AI Analytics. Because, of course, insights are needed in real-time so brands can respond while consumer emotions are still relevant.

How Does it Work?

The good news is, AI algorithms – the kind powering best-in-class tools – are fast and super accurate. Natural language processing (NLP) has evolved along with the technology that powers it – becoming more insightful and precise as AI has become more reliable.

There are two big reasons why:

  1. Algorithms are designed and monitored by humans – even if there’s an element of “learning” by the machine, it’s because a human programmed these things in that specific way.
  2. A combination of modalities bring the best of AI tech together for varying use cases.

That last point is paramount – and could be part of why brands distrust AI Analytics. In cases where social analytics tools are limited to a singular type of AI technology, data will be less reliable. Much less.

But best-in-class tools bring together expert systems, machine learning, and deep learning to more completely explore consumers’ hearts, making yesterday’s superficial analytics feel shabby indeed.

This is because these three types of AI tech are applied to the area where they work best, to collectively gather comprehensive data brands can use – immediately, and with confidence.

And when you want to know more, you can zoom in to the single-post level to see where the data was sourced. Not all tools offer that. Can you afford to blindly trust data you can’t see? We wouldn’t.


So, the real problem isn’t AI Analytics – it’s subpar AI Analytics. Be sure your tools are top-notch, and you’ll never have to question consumer sentiment – just respond to it. And your audience will love that.

For more on Artificial Intelligence Analytics, check out the rest of our AI Series:

Ready to see how AI Analytics work up close? Get in touch for a one-on-one demo!


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