Can Online Content Indicate an Individual's “Real‐Life” Personality?

ABSTRACT Assessing and analyzing personality plays a crucial role in an individual's holistic development. The evaluation of psychological attributes, such as the Big Five personality traits, has traditionally leaned heavily on standardized rating scales. Despite the numerous advantages associated with these scales, we suggest that a promising and innovative approach for assessing personality traits exists within the data available through online content available on persons. To determine whether online content can approximate traditional psychometric analysis, we utilized natural language processing (NLP) to predict the personality traits of 348 ( n = 348) individuals based on public content with an IPIP 50‐item psychometric survey assessment. Our results show that text content data from a range of online sources can indeed estimate the IPIP 50 outcomes of psychological surveys; an individual's online content actually reflects their “real life” personality traits. Our results indicate robustly that analyzing online content may be a reasonable proxy for traditional survey methods to reveal Big Five personality traits.