Emoji Analytics: A Social Listening How-To
Graphical iconography expresses what words can’t – and in a more economical manner. The language of emojis and emoticons has exploded and brands are beginning to discover emoji analytics to find the sentiment of messaging around their brand. Emojis have become part of our daily lives. When you’re rushing through the market between appointments and someone sends you good news, there’s no time to respond, ‘That’s amazing! I’m so happy for you.’ Instead, you just plop in a smiley face, hit send, and you’re on your way.
Businesses have largely ignored emojis – aside from some standard-bearers like Pepsi and Starbucks, who have created customized iconography for their brand advocates to share. But how do you track the analytics (volume and sentiment) around graphical imagery when social listening is built on a foundation of text analysis? As technology has progressed in synch with Moore’s Law, parsing and analyzing content on both the open and closed web has become faster and more efficient. Throw in a couple of algorithms and some machine learning and voila – your social listening dashboards are a cocktail of influencers, mentions – and emojis.
It’s important to understand the impact emojis and emoticons can have on a brand’s Social Listening analysis. The addition of a graphical layer of communication can turn a seemingly innocuous message into an expression of pure vitriol with the inclusion of several angry faces. An Instagram post which contains a brand-image tagged solely with an angel-face emoji immediately transforms from a neutral mention into positive sentiment.
Below are two business use cases which show the importance of emoji/emoticon detection and analysis to any company’s Social Listening program.
Sarcasm has long been a problem in machine analysis of human language. The subtext and tone of snark, innuendo, and irony can transform a seemingly positive message into one of bitter negativity. Take Instagram post above as an example. When analyzed through a pure text lens, the post seems overwhelmingly positive. However, if you’re a brand manager at Atlantis and you investigate into a bit more detail, you’ll find that the posted photo was far from #stunning (image recognition has even further to go than language analysis) and that the inclusion of two angry emojis flips good vibes to bad. A vertical that relies on good word of mouth and positive customer feedback to drive revenue simply cannot ignore the sentiment expressed by their patrons. Without emoji and emoticon detection and analysis, a sentiment-driven business misses daily opportunities to address problems with customer service.
If our developer isn’t using emoticon detection and he’s filtered his dashboard to show only positive mentions, he might miss his opportunity to connect with TheBlueBomber and nurture the relationship.
As you probably know by now, Synthesio recently announced our emoji analytics and emoticon analysis feature within our Social Listening platform, so if you want to learn more about this, and see how it works for yourself, then reach out and request a demo to see it in person!