Beyond Sentiment: The Value and Measurement of Consumer Certainty in Language

Sentiment analysis has fundamentally changed marketers’ ability to assess consumer opinion. Indeed, the measurement of attitudes via natural language has influenced how marketing is practiced on a day-to-day basis. Yet, recent findings suggest that sentiment analysis’s current emphasis on measuring valence (i.e., positivity or negativity) can produce incomplete, inaccurate, and even misleading insights. Conceptually, the current work challenges sentiment analysis to move beyond valence. We identify the certainty or confidence of consumers’ sentiment as a particularly potent facet to assess. Empirically, we develop a new computational measure of certainty in language – the Certainty Lexicon – and validate its use with sentiment analysis. To construct and validate this measure, we use text from 11.6 million people who generated billions of words, millions of online reviews, and hundreds of thousands of entries in an online prediction market. Across social media datasets, in-lab experiments, and online reviews, we find that the Certainty Lexicon is more comprehensive, generalizable, and accurate in its measurement compared to other tools. We also demonstrate the value of measuring sentiment certainty for marketers: certainty predicted the real-world success of commercials where traditional sentiment analysis did not. The Certainty Lexicon is available at www.CertaintyLexicon.com .