IBM Research Center Explores Deep Psychological Profiling on Twitter

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Researchers at IBM’s Almaden Research Center are looking to create “deep psychological profiles” of potential customers to better understand their values and needs. Dr. Eben Haber and his team are building off previous research by Tal Yarkoni that matched bloggers’ posts to the 5 modern dimensions of personality: extroversion, agreeableness, conscientiousness, neuroticism and openness to experience. Understanding these personality traits and how they relate to consumerism is critical for companies and brands because it can predict purchase: “Extroverts are more likely to respond to an advertisement for a mobile phone that promises excitement than one that promises convenience or security. They also prefer Coca-Cola to Pepsi and Maybelline cosmetics to Max Factor. Agreeable people though, tend to prefer Pepsi…”

Dr. Haber’s team is taking the Yarkoni research one step further by using linguistic signifiers to understand value systems. They have developed software that analyzes a stream of tweets and searches for words that reflect a user’s values (e.g. loyalty, self-enhancement) and needs (e.g. excitement, control). So far they have analyzed data for 90MM users and have found that they can reasonably predict a user’s personality and value traits from only 50 tweets.

As brands battle one another for the edge on Big Data, the importance of deep psychological research like the kind Dr. Haber is exploring will only become more significant. “What are people talking about on social?”  is a question very easily answered, and unfortunately, the results aren’t always as valuable as one would think. “Why are people talking about what they talk about on social and what does it say about how they will respond to advertising?” is a much more difficult problem to solve, but consequently, yields a much bigger and much more lucrative reward. Can Dr. Haber really tell us how we think about the purchases we make by analyzing a bunch of Tweets? Either way, marketing might never be the same again.

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