Abstract
We used quantitative semantics to find clusters of words in LinkedIn users' self-descriptions to an employer or a friend. Some of these clusters discriminated between worker and friend conditions (e.g., flexible vs. caring) and between LinkedIn users with high and low education (e.g., analytical vs. messy).
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