Leveraging 4Sight’s Emotional Lexicon Meter™ to Reveal How Each Broke Thru
Super Bowl advertising is of course all about evoking emotion, but it’s not always easy to understand what emotions different ads elicit. 4Sight’s Emotional Lexicon Metric™ does just that – in this case mining user generated content for the Trump & Bloomberg Super Bowl ads – to measure how online comments are evoking 7 different emotions. And one conclusion is clear: the Bloomberg ad stirs up stronger emotional responses of fear, anger, disgust and sadness, whereas Trump evokes lower emotions around these same emotions and just slightly higher levels of joy. And some verbatim comments give a hint to some of the reason why.
Methodology of 4Sight’s Emotional Lexicon Meter™
The 4Sight Emotional Lexicon Meter™ leverages a combination of text analytics, natural language processing and the NRC lexicon to mine user generated content for the emotions evoked by each ad. The lexicon leverages crowdsourced emotional word associations to extract emotional connections to Fear, Anger, Joy, Anticipation, Sadness, Disgust and Trust. In this case, 4Sight mined thousands of comments from social media and blogs responding to the two ads to extract an understanding of the 7 different emotions elicited by the ads. This alone does not tell you the “why behind the what” – e.g. why one ad evokes more fear or less fear– that requires a deeper dive, but it does provide a foundation for understanding what messages are resonating with viewers.
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